- TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.

Throughout the 8 modules in this course you will learn about fundamental conc...
Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.

Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning.

Each of these modules include in-depth explanations and a variety of different coding examples. After completing this course you will have a thorough knowledge of the core techniques in machine learning and AI and have the skills necessary to apply these techniques to your own data-sets and unique problems.


⭐️ Google Colaboratory Notebooks ⭐️

📕 Module 2: Introduction to TensorFlow - https://colab.research.google.com/drive/1F_EWVKa8rbMXi3_fG0w7AtcscFq7Hi7B#forceEdit=true&sandboxMode=true
📗 Module 3: Core Learning Algorithms - https://colab.research.google.com/drive/15Cyy2H7nT40sGR7TBN5wBvgTd57mVKay#forceEdit=true&sandboxMode=true
📘 Module 4: Neural Networks with TensorFlow - https://colab.research.google.com/drive/1m2cg3D1x3j5vrFc-Cu0gMvc48gWyCOuG#forceEdit=true&sandboxMode=true
📙 Module 5: Deep Computer Vision - https://colab.research.google.com/drive/1ZZXnCjFEOkp_KdNcNabd14yok0BAIuwS#forceEdit=true&sandboxMode=true
📔 Module 6: Natural Language Processing with RNNs - https://colab.research.google.com/drive/1ysEKrw_LE2jMndo1snrZUh5w87LQsCxk#forceEdit=true&sandboxMode=true
📒 Module 7: Reinforcement Learning - https://colab.research.google.com/drive/1IlrlS3bB8t1Gd5Pogol4MIwUxlAjhWOQ#forceEdit=true&sandboxMode=true


⭐️ Course Contents ⭐️

⌨️ (00:03:25) Module 1: Machine Learning Fundamentals
⌨️ (00:30:08) Module 2: Introduction to TensorFlow
⌨️ (01:00:00) Module 3: Core Learning Algorithms
⌨️ (02:45:39) Module 4: Neural Networks with TensorFlow
⌨️ (03:43:10) Module 5: Deep Computer Vision - Convolutional Neural Networks
⌨️ (04:40:44) Module 6: Natural Language Processing with RNNs
⌨️ (06:08:00) Module 7: Reinforcement Learning with Q-Learning
⌨️ (06:48:24) Module 8: Conclusion and Next Steps


⭐️ About the Author ⭐️

The author of this course is Tim Ruscica, otherwise known as “Tech With Tim” from his educational programming YouTube channel. Tim has a passion for teaching and loves to teach about the world of machine learning and artificial intelligence. Learn more about Tim from the links below:
🔗 YouTube: https://www.youtube.com/channel/UC4JX40jDee_tINbkjycV4Sg
🔗 LinkedIn: https://www.linkedin.com/in/tim-ruscica/

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news
Intro - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Intro

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:00:00 - 00:03:24
Hi! I'm  hours in, I am learning to work with tf in University, so I already knew most of the things he showed until then. I am specifically looking for an explanation of tensorflow ops and how to create custom ones. Is this covered in this class at some point? Or do you know where I can find a tutorial on this (other than tf's documentation)? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Hi! I'm hours in, I am learning to work with tf in University, so I already knew most of the things he showed until then. I am specifically looking for an explanation of tensorflow ops and how to create custom ones. Is this covered in this class at some point? Or do you know where I can find a tutorial on this (other than tf's documentation)?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:02:45 - 06:52:08
ML Fundamentals - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

ML Fundamentals

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:03:24 - 00:30:29
: Machine Learning Fundamentals () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Machine Learning Fundamentals ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:03:25 - 00:30:08
: Machine Learning Fundamentals (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Machine Learning Fundamentals (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:03:25 - 00:30:08
⌨️ () Module 1: Machine Learning Fundamentals - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 1: Machine Learning Fundamentals

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:03:25 - 00:30:08
~Introduction. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

~Introduction.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:03:30 - 06:52:08
“I am not artistic whatsoever” - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

“I am not artistic whatsoever”

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:04:00 - 00:27:00
tf.keras.layers.LSTM(32) is not equal to the size of the embedding word ! It is the size of output of LSTM.You could have tf.keras.layers.LSTM(64) for example - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

tf.keras.layers.LSTM(32) is not equal to the size of the embedding word ! It is the size of output of LSTM.You could have tf.keras.layers.LSTM(64) for example

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:05:17 - 06:52:08
At  you said labels are the output information we get by predicting from features and at 18:36 you say that features and labels are combined to get the output we need. Its pretty confusing. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At you said labels are the output information we get by predicting from features and at 18:36 you say that features and labels are combined to get the output we need. Its pretty confusing.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:17:23 - 06:52:08
.import tensorflow as tfprint(tf.__version__) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

.import tensorflow as tfprint(tf.__version__)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:18:03 - 06:52:08
Isn't the diagram at  an example of Clustering?I always thought the output for Unsupervised Learning was not present and the model learns from trial and error pattern.I don't see a direct link between unsupervised learning and Clustering.Please can someone clear my doubts? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Isn't the diagram at an example of Clustering?I always thought the output for Unsupervised Learning was not present and the model learns from trial and error pattern.I don't see a direct link between unsupervised learning and Clustering.Please can someone clear my doubts?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:24:15 - 06:52:08
@ And that is how they build the Matrix. Great video. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

@ And that is how they build the Matrix. Great video.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:26:23 - 06:52:08
Does enviorment equals to state? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Does enviorment equals to state?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:26:57 - 06:52:08
taking a leak - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

taking a leak

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:27:00 - 00:27:49
humping a pole - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

humping a pole

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:27:49 - 06:52:08
the agent at  is a pole dancer.  Really enjoying the content brother! Great job.  You have already destroyed any college professor I have experienced. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

the agent at is a pole dancer. Really enjoying the content brother! Great job. You have already destroyed any college professor I have experienced.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:28:13 - 06:52:08
He just missed the chance to end the introduction perfectly at - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

He just missed the chance to end the introduction perfectly at

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:30:00 - 06:52:08
: Introduction to TensorFlow () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Introduction to TensorFlow ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:30:08 - 01:00:00
: Introduction to TensorFlow (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Introduction to TensorFlow (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:30:08 - 01:00:00
⌨️ () Module 2: Introduction to TensorFlow - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 2: Introduction to TensorFlow

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:30:08 - 01:00:00
Intro to Tensorflow - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Intro to Tensorflow

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:30:29 - 06:52:08
. TensorFlow has two main components: graph and session - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

. TensorFlow has two main components: graph and session

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:33:05 - 05:56:31
I didn't understand that. can someone please try to explain it to me? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I didn't understand that. can someone please try to explain it to me?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:33:12 - 06:52:08
:Failed  Reason: No Water/late    Time in: - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

:Failed Reason: No Water/late Time in:

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:38:04 - 06:52:08
Physics: a tensor is something that transforms like a tensor - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Physics: a tensor is something that transforms like a tensor

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:43:28 - 06:52:08
don't mind me, just reminding myself - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

don't mind me, just reminding myself

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:46:55 - 06:52:08
at   you have to explicitly mention, dtype=tf.int16, else it doesn't consider the argumentINPUT - tensor_int2 = tf.Variable(200, dtype=tf.int64)OUTPUT - <tf.Variable 'Variable:0' shape=() dtype=int64, numpy=200> andINPUT  - tensor_int3 = tf.Variable(300, tf.int16),OUTPUT - <tf.Variable 'Variable:0' shape=() dtype=int32, numpy=300> - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

at you have to explicitly mention, dtype=tf.int16, else it doesn't consider the argumentINPUT - tensor_int2 = tf.Variable(200, dtype=tf.int64)OUTPUT - <tf.Variable 'Variable:0' shape=() dtype=int64, numpy=200> andINPUT - tensor_int3 = tf.Variable(300, tf.int16),OUTPUT - <tf.Variable 'Variable:0' shape=() dtype=int32, numpy=300>

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:46:57 - 06:52:08
rank - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

rank

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:48:00 - 00:50:00
why does it say dtype = int32 in <tf.Tensor: shape=(), dtype=int32, numpy=2>,even thou he set it to tf.string ?can anyone explain pleas. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

why does it say dtype = int32 in <tf.Tensor: shape=(), dtype=int32, numpy=2>,even thou he set it to tf.string ?can anyone explain pleas.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:49:36 - 06:52:08
why is the dtype int32 despite the variable being a string type? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

why is the dtype int32 despite the variable being a string type?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:49:46 - 06:52:08
shape - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

shape

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:50:00 - 00:52:00
@ the shape explanation is wrong. You have a 2 by 2 shape for the rank2 variable because you have 2 elements in 2 lists/arrays, not because you have 2 elements in each of the lists (i.e. you could have 2 elements in 3 lists and have a 3 by 2 shape). - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

@ the shape explanation is wrong. You have a 2 by 2 shape for the rank2 variable because you have 2 elements in 2 lists/arrays, not because you have 2 elements in each of the lists (i.e. you could have 2 elements in 3 lists and have a 3 by 2 shape).

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:50:35 - 06:52:08
At  the way you suggested to get a rank three tensor gave an error --rank2_tensor = tf.Variable([["test", "ok", ["ok","oj"]]],["test", "yes", ["zyx", "oj"]]], tf.string) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At the way you suggested to get a rank three tensor gave an error --rank2_tensor = tf.Variable([["test", "ok", ["ok","oj"]]],["test", "yes", ["zyx", "oj"]]], tf.string)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:51:47 - 06:52:08
change in shape - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

change in shape

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:52:00 - 00:55:10
manual save - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

manual save

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:52:18 - 06:52:08
thing at  , can anyone help me out!😭 - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

thing at , can anyone help me out!😭

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:54:25 - 06:52:08
types of tensors - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

types of tensors

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:55:10 - 00:56:30
evaluating Tensors - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

evaluating Tensors

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:56:30 - 00:57:25
For running seesions  at :with tf.compat.v1.Session() as sess:print(tensor0.eval()) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

For running seesions at :with tf.compat.v1.Session() as sess:print(tensor0.eval())

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:57:03 - 06:52:08
sources - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

sources

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:57:25 - 00:57:40
practice - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

practice

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:57:40 - 01:00:00
we have 125 of 5 vectors not 5 vectors of 125 - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

we have 125 of 5 vectors not 5 vectors of 125

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
00:59:20 - 06:52:08
: Core Learning Algorithms () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Core Learning Algorithms ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 02:45:39
: Core Learning Algorithms (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Core Learning Algorithms (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 02:45:39
Hey just to confirm, are you sure the  is the linear regression and not linear classification. i am not able to get this. we are classifying whether it will be survived or not. based on the input data. can some one please help with this - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Hey just to confirm, are you sure the is the linear regression and not linear classification. i am not able to get this. we are classifying whether it will be survived or not. based on the input data. can some one please help with this

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 06:52:08
Linear Regression  () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Linear Regression ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 01:54:00
This end-to-end walkthrough trains a logistic regression model (binary classification and not a regression) using the tf.estimator API. The model is often used as a baseline for other, more complex, algorithms.I guess it is not a regression problem but it is the classification problem - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

This end-to-end walkthrough trains a logistic regression model (binary classification and not a regression) using the tf.estimator API. The model is often used as a baseline for other, more complex, algorithms.I guess it is not a regression problem but it is the classification problem

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 06:52:08
tensorflow core learning algorithms - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

tensorflow core learning algorithms

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 01:02:40
⌨️ () Module 3: Core Learning Algorithms - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 3: Core Learning Algorithms

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:00 - 02:45:39
= tensor[]  # selects second and fourth rowprint(row2and4) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

= tensor[] # selects second and fourth rowprint(row2and4)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:02 - 06:52:08
Great Video (even if i havent finished it yet)! The example in  is NOT regression is Classification. You have 2 classes (survived or not) and you try to classify the passengers. In other words, the result would always be a probability, you cannot use the same methodology to predict the age, for example . - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Great Video (even if i havent finished it yet)! The example in is NOT regression is Classification. You have 2 classes (survived or not) and you try to classify the passengers. In other words, the result would always be a probability, you cannot use the same methodology to predict the age, for example .

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:00:10 - 06:52:08
linear regression - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

linear regression

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:02:40 - 01:13:00
"Do not Memorize just Understand" - made my mind to stay "calm". Felt to thank at that time frame... "Thank You!" - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

"Do not Memorize just Understand" - made my mind to stay "calm". Felt to thank at that time frame... "Thank You!"

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:02:44 - 06:52:08
thanks for the explanation at ! - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

thanks for the explanation at !

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:06:06 - 06:52:08
at  he fitted best fit line not the plane in 3d graph in linear regression algorithm RIP mathematics.😥😥 - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

at he fitted best fit line not the plane in 3d graph in linear regression algorithm RIP mathematics.😥😥

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:10:59 - 06:52:08
() Wouldn't linear regression in 3D give you a plane rather than a line? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

() Wouldn't linear regression in 3D give you a plane rather than a line?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:11:00 - 06:52:08
Around  the "line of best fit" with two predictor variables should be a plane, no? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Around the "line of best fit" with two predictor variables should be a plane, no?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:11:11 - 06:52:08
D you're supposed to fit the best plane, not the line. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

D you're supposed to fit the best plane, not the line.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:11:13 - 06:52:08
BIG correction: In 3 dimensions we are trying to fit a 2d plane through the points NOT a single line. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

BIG correction: In 3 dimensions we are trying to fit a 2d plane through the points NOT a single line.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:12:00 - 06:52:08
Bookmark - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Bookmark

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:12:50 - 06:52:08
How is it possible to get out the parameters for the equation, after training in the case of the Titanic dataset (see from )? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

How is it possible to get out the parameters for the equation, after training in the case of the Titanic dataset (see from )?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:13:00 - 06:52:08
setup and import - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

setup and import

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:13:00 - 01:15:40
@ you did not mention what the 'from six.moves import urllib stands for.  Was curious what that was? It's possible you accidentally skipped over this one.  You can always add an annotation on the video if you know the answer so it shows for others. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

@ you did not mention what the 'from six.moves import urllib stands for. Was curious what that was? It's possible you accidentally skipped over this one. You can always add an annotation on the video if you know the answer so it shows for others.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:15:00 - 06:52:08
data - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

data

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:15:40 - 06:52:08
the fare around  referred to the amount of money they paid to travel on the boat. A fare is a payment made for a trip. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

the fare around referred to the amount of money they paid to travel on the boat. A fare is a payment made for a trip.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:19:00 - 06:52:08
Parch stands for number of parents and children aboardFare was obviously the price passengers had to pay for the journey - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Parch stands for number of parents and children aboardFare was obviously the price passengers had to pay for the journey

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:19:31 - 06:52:08
in  you say that  "Name" says wether a person has survived or not. This doesn't seem to be true. When you do "dftrain.loc[2]" "Name" is 2. Also it can't be true since we deleted the column from our dataframe. "Name" just tells you the index of the row. In this example the first one. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

in you say that "Name" says wether a person has survived or not. This doesn't seem to be true. When you do "dftrain.loc[2]" "Name" is 2. Also it can't be true since we deleted the column from our dataframe. "Name" just tells you the index of the row. In this example the first one.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:25:30 - 06:52:08
At  print(dftrain.loc[0], y_train.loc[0]) actually only prints the value of dftrain.loc[0] and Name:0 just refers to the index of the entry. If you want to display y_train.loc[0] you have to print it seperately with print(y_train.loc[0]) or print(y_train[0]) (both work) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At print(dftrain.loc[0], y_train.loc[0]) actually only prints the value of dftrain.loc[0] and Name:0 just refers to the index of the entry. If you want to display y_train.loc[0] you have to print it seperately with print(y_train.loc[0]) or print(y_train[0]) (both work)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:25:38 - 06:52:08
I think that is not the "encoded value" rather the real unique number of sibling, same with the "parch". Now I am wondering is TF feature column really encode categorical features, or just making a literal feature column from the vocab? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I think that is not the "encoded value" rather the real unique number of sibling, same with the "parch". Now I am wondering is TF feature column really encode categorical features, or just making a literal feature column from the vocab?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:36:34 - 06:52:08
Well I suppose they've to add this function as an external command in tensorflow v.3.0 would be greatly helpful - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Well I suppose they've to add this function as an external command in tensorflow v.3.0 would be greatly helpful

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:41:07 - 06:52:08
why does it need to be a function inside a function, though? Can't this be reduced to a single function? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

why does it need to be a function inside a function, though? Can't this be reduced to a single function?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:43:30 - 06:52:08
I was actually hoping to hear an explanation for the need of an input function and not just a remark to read the documentation - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I was actually hoping to hear an explanation for the need of an input function and not just a remark to read the documentation

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:43:32 - 06:52:08
I don't really see the use of make_input_fn.  You could just use one input_function with different arguments for test and train. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I don't really see the use of make_input_fn. You could just use one input_function with different arguments for test and train.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:43:39 - 06:52:08
Do I need to write the same line of code as in   for my every Machine Learning problem? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Do I need to write the same line of code as in for my every Machine Learning problem?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:43:58 - 06:52:08
"We're  not trining it... we're just training it"  ;D - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

"We're not trining it... we're just training it" ;D

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:44:11 - 06:52:08
creating a model with titanic dataset - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

creating a model with titanic dataset

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:44:30 - 06:52:08
Can someone clear my confusion at  he use linearClassifier and the dataset he used have a categorical label which shows it is a classification problem up till now ok, however at the moment he is discussing regression so he should use linearRegressor?  this is more confusing at  2:02:16 when he discusses the difference between classification and regression. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Can someone clear my confusion at he use linearClassifier and the dataset he used have a categorical label which shows it is a classification problem up till now ok, however at the moment he is discussing regression so he should use linearRegressor? this is more confusing at 2:02:16 when he discusses the difference between classification and regression.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:44:35 - 06:52:08
of this course (core learning) but there is something not clear in my mind,  why a .LinearClassifier is used? is it for linear regression algorithms or a for linear classifier ones? the goal is to find a line that fits the dataset or a line that "splits" it? pls halp - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

of this course (core learning) but there is something not clear in my mind, why a .LinearClassifier is used? is it for linear regression algorithms or a for linear classifier ones? the goal is to find a line that fits the dataset or a line that "splits" it? pls halp

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:45:00 - 06:52:08
Edit: Me literally dancing just because I got better accuracy at  XD - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Edit: Me literally dancing just because I got better accuracy at XD

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:46:47 - 06:52:08
Congratulations to those who reached this part. You've just created a machine learning program. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Congratulations to those who reached this part. You've just created a machine learning program.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:47:06 - 06:52:08
Thank you for the time and effort. Helps me a lot. But,  You talk about probabilities of "survived" and "did not survive". Two classes, but the sample says this is regression. Isn't it a classification problem?  Shouldn't a regression be predicting a number which is the chance of survival as a single number? Thank you. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Thank you for the time and effort. Helps me a lot. But, You talk about probabilities of "survived" and "did not survive". Two classes, but the sample says this is regression. Isn't it a classification problem? Shouldn't a regression be predicting a number which is the chance of survival as a single number? Thank you.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:51:39 - 06:52:08
Checkpoint - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Checkpoint

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:54:00 - 06:52:08
Classification () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Classification ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
01:54:00 - 02:17:07
is there any particular reason why we didn't just create an inner function previously or is using lamba just clearer coding? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

is there any particular reason why we didn't just create an inner function previously or is using lamba just clearer coding?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:06:54 - 06:52:08
You say 0.39 is pretty bad:me looks at my loss: *sees 0.948* - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

You say 0.39 is pretty bad:me looks at my loss: *sees 0.948*

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:08:44 - 06:52:08
around - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

around

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:11:05 - 06:52:08
Around  isdigit() will not really work. In you case it worked because you didn't enter an alphanumeric value as input. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Around  isdigit() will not really work. In you case it worked because you didn't enter an alphanumeric value as input.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:14:00 - 06:52:08
The code you use at the end of the classifcation model around  to insert the values and get the prediction, is it possible to do that same code for a dnnregressor? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

The code you use at the end of the classifcation model around to insert the values and get the prediction, is it possible to do that same code for a dnnregressor?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:14:14 - 06:52:08
K-Means Clustering () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

K-Means Clustering ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:17:07 - 02:24:56
Hidden Markov Models () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Hidden Markov Models ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:24:56 - 06:52:08
Ignore this just saving my prog - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Ignore this just saving my prog

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:35:34 - 06:52:08
at , it's accidentally backwards in the ipynb file. "initial_distribution = tfd.Categorical(probs=[0.2, 0.8])" should be [0.8, 0.2] like in the video. Actually, all the numbers in that code block are mismatched from the video and don't match the weather diagram. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

at , it's accidentally backwards in the ipynb file. "initial_distribution = tfd.Categorical(probs=[0.2, 0.8])" should be [0.8, 0.2] like in the video. Actually, all the numbers in that code block are mismatched from the video and don't match the weather diagram.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:36:20 - 06:52:08
: Neural Networks with TensorFlow () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Neural Networks with TensorFlow ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:45:39 - 03:43:10
: Neural Networks with TensorFlow (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Neural Networks with TensorFlow (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:45:39 - 03:43:10
⌨️ () Module 4: Neural Networks with TensorFlow - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 4: Neural Networks with TensorFlow

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:45:39 - 03:43:10
NN starts here. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

NN starts here.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
02:46:35 - 06:52:08
I have a question at  if the value of a neuron in the next layer is calculated by Ewi xi + b. That means all the neurons in the next layer will have the same value because the same calculation will be carried out since wi ni and b will be gotten from the previous layer for each neuron. Can someone please explain this I think I have the wrong ideas - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I have a question at if the value of a neuron in the next layer is calculated by Ewi xi + b. That means all the neurons in the next layer will have the same value because the same calculation will be carried out since wi ni and b will be gotten from the previous layer for each neuron. Can someone please explain this I think I have the wrong ideas

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:02:47 - 06:52:08
I like your example of sigmod which provides more dimensions to the network capability at , which will lead to better predictions. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I like your example of sigmod which provides more dimensions to the network capability at , which will lead to better predictions.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:08:10 - 06:52:08
.If someone is confused how we can get better features at higher dimensions. I understood it in this way.Think that there is bad point in 2 dimensions (like in a square or a circle ) , now when we shift the same bad point to 3 dimensions or 4 dimensions .They take the shape of something like a cube or sphere which increases the size of the bad point. Similarly , when extracting features at higher dimensions can yield to better features. I hope it helps :) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

.If someone is confused how we can get better features at higher dimensions. I understood it in this way.Think that there is bad point in 2 dimensions (like in a square or a circle ) , now when we shift the same bad point to 3 dimensions or 4 dimensions .They take the shape of something like a cube or sphere which increases the size of the bad point. Similarly , when extracting features at higher dimensions can yield to better features. I hope it helps :)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:09:00 - 06:52:08
i dont' thing cost and loss are the same thing. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

i dont' thing cost and loss are the same thing.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:12:33 - 06:52:08
You can display the image in greyscale like this: `plt.imshow(train_images[0], cmap="gray")` - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

You can display the image in greyscale like this: `plt.imshow(train_images[0], cmap="gray")`

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:23:50 - 06:52:08
On  you train the neural network with 10 and than 8 and than 1 epoch but its actually still the same model you train, thats why the loss on start is quite low already. So basically you did a epochs=19 run - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

On you train the neural network with 10 and than 8 and than 1 epoch but its actually still the same model you train, thats why the loss on start is quite low already. So basically you did a epochs=19 run

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:33:00 - 06:52:08
overfitting example : - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

overfitting example :

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:34:42 - 06:52:08
Just a heads up, there was a mistake at  - you forgot to reinitialize the "model"! - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Just a heads up, there was a mistake at - you forgot to reinitialize the "model"!

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:35:00 - 06:52:08
When you were fitting the model around , it looked like each run of model.fit() was actually running from the previously fit model, rather than on a fresh, unfit model. So essentially the first run had a total of 10 epochs, then 18, then 19, rather than 10, 8, and 1 like you seemed to think. I don't know if you caught this later in the video, but it didn't seem like you did here. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

When you were fitting the model around , it looked like each run of model.fit() was actually running from the previously fit model, rather than on a fresh, unfit model. So essentially the first run had a total of 10 epochs, then 18, then 19, rather than 10, 8, and 1 like you seemed to think. I don't know if you caught this later in the video, but it didn't seem like you did here.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:35:00 - 06:52:08
You said, epoch used to split big dataset into small one. but at  , you have 60k images dataset and each epoch processing 60k images. how?? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

You said, epoch used to split big dataset into small one. but at , you have 60k images dataset and each epoch processing 60k images. how??

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:35:00 - 06:52:08
Just a comment, on , when you train the network again it's not re-training from scratch but instead using the weights it already had. Unless you manually reset the graph, you'll be training for the sum of all epochs you used the fit function (like 10 + 8 + 1 epochs)To avoid this problem you should use something like keras.backend.clear_session() or tf.reset_default_graph() between tests with hyperparameters 😉 - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Just a comment, on , when you train the network again it's not re-training from scratch but instead using the weights it already had. Unless you manually reset the graph, you'll be training for the sum of all epochs you used the fit function (like 10 + 8 + 1 epochs)To avoid this problem you should use something like keras.backend.clear_session() or tf.reset_default_graph() between tests with hyperparameters 😉

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:36:44 - 06:52:08
At , when you said with less epochs, you are getting better test results. Which is actually not the case. You first run for 10 epochs, your weights got updated. Then again you run 8 epochs, your weights improved from previous values onwards.. so that eventually makes 18 epochs.. then you run for 1 epoch, which makes it 19 epochs.. so in this case, after 19th epoch, your accuracy on test data is increased. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At , when you said with less epochs, you are getting better test results. Which is actually not the case. You first run for 10 epochs, your weights got updated. Then again you run 8 epochs, your weights improved from previous values onwards.. so that eventually makes 18 epochs.. then you run for 1 epoch, which makes it 19 epochs.. so in this case, after 19th epoch, your accuracy on test data is increased.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:00 - 06:52:08
Not sure if it is already discussed or not. At  you updated the model by running the same cell for multiple epochs. There the previous model got updated and thus accuracy improved. Not that, with less epoch the accuracy is high. Thanks :) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Not sure if it is already discussed or not. At you updated the model by running the same cell for multiple epochs. There the previous model got updated and thus accuracy improved. Not that, with less epoch the accuracy is high. Thanks :)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:00 - 06:52:08
Okay I'm not completely sure about this so take it with a grain of salt but I don't think you're hyperparameter/epoch tuning at  is doing what you expect. With jupyter notebooks, it saves the models and each time you run an epoch, it continues tuning the previous weights. In order to really display epoch differences, you need to restart the runtime and repeat the process. If you notice, each time you run the code, the "first epoch accuracy" increases significantly. The first time you ran it, the accuracy was 83% after the first epoch. After the 10th, it was 90.6%. Then, for the next iteration (8 epochs), the accuracy was 91.2% after the first epoch. Then, when running on just a single epoch, it started at 93%. Likely this is because the model continued to train an additional 9 epochs. So, in fact, the single epoch data is ironically quite overfitting. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Okay I'm not completely sure about this so take it with a grain of salt but I don't think you're hyperparameter/epoch tuning at is doing what you expect. With jupyter notebooks, it saves the models and each time you run an epoch, it continues tuning the previous weights. In order to really display epoch differences, you need to restart the runtime and repeat the process. If you notice, each time you run the code, the "first epoch accuracy" increases significantly. The first time you ran it, the accuracy was 83% after the first epoch. After the 10th, it was 90.6%. Then, for the next iteration (8 epochs), the accuracy was 91.2% after the first epoch. Then, when running on just a single epoch, it started at 93%. Likely this is because the model continued to train an additional 9 epochs. So, in fact, the single epoch data is ironically quite overfitting.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:00 - 06:52:08
Run time  - I think we have to compile the model every time before we do a fit. Otherwise it just memorize the previous epochs and use it for next iterations. In this case I believe that 92% accuracy of 1 epochs is the same as the addition of previous epochs i.e 10+8+1 = 19 epochs - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Run time - I think we have to compile the model every time before we do a fit. Otherwise it just memorize the previous epochs and use it for next iterations. In this case I believe that 92% accuracy of 1 epochs is the same as the addition of previous epochs i.e 10+8+1 = 19 epochs

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:00 - 06:52:08
Training on one epoch in this case builds on already existing model that was created using many epochs. You need to recreate the model to demonstrate this - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Training on one epoch in this case builds on already existing model that was created using many epochs. You need to recreate the model to demonstrate this

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:01 - 06:52:08
At ... actually the code has run for  19 times on the train data and three time on test data... to check it over need to reset model or reset runtime... - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At ... actually the code has run for 19 times on the train data and three time on test data... to check it over need to reset model or reset runtime...

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:10 - 06:52:08
On  you need to reset your NN by running again the code that defines it, and then train it using less epochs. Otherwise the epochs just accumulate. This is why you see an increasing accuracy every time you run. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

On you need to reset your NN by running again the code that defines it, and then train it using less epochs. Otherwise the epochs just accumulate. This is why you see an increasing accuracy every time you run.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:11 - 06:52:08
For some reason it appears 7/7 when im trainning the model but my dataset is 200, and your is 60,000 and it clearly shows you 60000/60000 - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

For some reason it appears 7/7 when im trainning the model but my dataset is 200, and your is 60,000 and it clearly shows you 60000/60000

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:20 - 06:52:08
I think you just trained the previously trained model. - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I think you just trained the previously trained model.

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:28 - 06:52:08
Hi great course. However I noticed one explanation that is not correct regarding over fitting at time dnn example : over fitting vs. number of epochs. (you tried 10 then 8 then 1 epoch) . Actually that is not correct as each time you run , you continue from the last checkpoint . So first time you have epoch 0-10, then 10-18 and finally 18-19. Hope it helps! - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Hi great course. However I noticed one explanation that is not correct regarding over fitting at time dnn example : over fitting vs. number of epochs. (you tried 10 then 8 then 1 epoch) . Actually that is not correct as each time you run , you continue from the last checkpoint . So first time you have epoch 0-10, then 10-18 and finally 18-19. Hope it helps!

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:37:40 - 06:52:08
At   ... why the prediction = model.prediction(np.array([image])) instead of prediction  = model.prediction(image) ?. The image are already in array right if im not mistaken - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At ... why the prediction = model.prediction(np.array([image])) instead of prediction = model.prediction(image) ?. The image are already in array right if im not mistaken

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:42:10 - 06:52:08
I run this code, but it doesn't give me expected and guess. It just give me the picture. Why? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

I run this code, but it doesn't give me expected and guess. It just give me the picture. Why?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:42:43 - 06:52:08
: Deep Computer Vision - Convolutional Neural Networks () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Deep Computer Vision - Convolutional Neural Networks ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:43:10 - 04:40:44
: Deep Computer Vision - Convolutional Neural Networks (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Deep Computer Vision - Convolutional Neural Networks (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:43:10 - 04:40:44
⌨️ () Module 5: Deep Computer Vision - Convolutional Neural Networks - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 5: Deep Computer Vision - Convolutional Neural Networks

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
03:43:10 - 04:40:44
Why are we using a activation function in CNN, we use pooling to reduce the dimension but an activation function increases the dimension as was said before ? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Why are we using a activation function in CNN, we use pooling to reduce the dimension but an activation function increases the dimension as was said before ?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:11:45 - 06:52:08
Can someone please tell why he has validated the data while fitting the model? Any significance? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Can someone please tell why he has validated the data while fitting the model? Any significance?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:16:30 - 06:52:08
what is disable progress bar - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

what is disable progress bar

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:25:30 - 06:52:08
Could anyone help me, telling me which is the color correction function he is talking about at  and where it should be placed? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Could anyone help me, telling me which is the color correction function he is talking about at and where it should be placed?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:28:15 - 06:52:08
Does somebody know the missing code -> which messes up the color at ? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Does somebody know the missing code -> which messes up the color at ?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:28:38 - 06:52:08
Can someone explain to me where the number 32 comes from? The note says "The 32 means that we have 32 layers of differnt filters/features." Why is that? My understanding is that the size here (32,5,5,1280) has only to do with the last layer. Why Tim uses "layers" in his note? Thanks a lot! - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Can someone explain to me where the number 32 comes from? The note says "The 32 means that we have 32 layers of differnt filters/features." Why is that? My understanding is that the size here (32,5,5,1280) has only to do with the last layer. Why Tim uses "layers" in his note? Thanks a lot!

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:31:00 - 06:52:08
At , Tim said that the no of trainable parameters is zero because we get .trainable = False , but its value is already zero if you see the output before.Can someone explain this to me ?Thanks a lot in advance - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

At , Tim said that the no of trainable parameters is zero because we get .trainable = False , but its value is already zero if you see the output before.Can someone explain this to me ?Thanks a lot in advance

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:32:24 - 06:52:08
: Natural Language Processing with RNNs () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Natural Language Processing with RNNs ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:40:44 - 06:08:00
: Natural Language Processing with RNNs (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Natural Language Processing with RNNs (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:40:44 - 06:08:00
⌨️ () Module 6: Natural Language Processing with RNNs - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 6: Natural Language Processing with RNNs

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
04:40:44 - 06:08:00
. how did you get VOCAB_SIZE? - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

. how did you get VOCAB_SIZE?

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
05:13:41 - 06:52:08
. We can rebuild a model and change its original parameters - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

. We can rebuild a model and change its original parameters

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
05:56:31 - 06:08:00
. Reinforcement learning with Q-Learning - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

. Reinforcement learning with Q-Learning

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:08:00 - 06:52:08
: Reinforcement Learning with Q-Learning () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Reinforcement Learning with Q-Learning ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:08:00 - 06:48:24
: Reinforcement Learning with Q-Learning (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Reinforcement Learning with Q-Learning (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:08:00 - 06:48:24
⌨️ () Module 7: Reinforcement Learning with Q-Learning - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 7: Reinforcement Learning with Q-Learning

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:08:00 - 06:48:24
Timestamp for me: - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

Timestamp for me:

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:30:00 - 06:52:08
, dont update the Q table? which means we use pretrain table? dont write that line of code? Or you are saying something else.  I am not sure what it mean - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

, dont update the Q table? which means we use pretrain table? dont write that line of code? Or you are saying something else. I am not sure what it mean

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:47:38 - 06:52:08
: Conclusion and Next Steps () - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Conclusion and Next Steps ()

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:48:24 - 06:52:08
: Conclusion and Next Steps (​) - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

: Conclusion and Next Steps (​)

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:48:24 - 06:52:08
⌨️ () Module 8: Conclusion and Next Steps - TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

⌨️ () Module 8: Conclusion and Next Steps

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
2020年03月04日 
06:48:24 - 06:52:08

freeCodeCamp.org

※本サイトに掲載されているチャンネル情報や動画情報はYouTube公式のAPIを使って取得・表示しています。

Timetable

動画タイムテーブル

動画数:1631件

⌨️ () Overview - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Overview

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:00:00 - 00:05:53
⌨️ () Indexing - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Indexing

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:05:53 - 00:10:40
⌨️ () Retrieval - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Retrieval

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:10:40 - 00:15:52
⌨️ () Generation - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Generation

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:15:52 - 00:22:14
⌨️ () Query Translation (Multi-Query) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Translation (Multi-Query)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:22:14 - 00:28:20
⌨️ () Query Translation (RAG Fusion) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Translation (RAG Fusion)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:28:20 - 00:33:57
⌨️ () Query Translation (Decomposition) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Translation (Decomposition)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:33:57 - 00:40:31
⌨️ () Query Translation (Step Back) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Translation (Step Back)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:40:31 - 00:47:24
⌨️ () Query Translation (HyDE) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Translation (HyDE)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:47:24 - 00:52:07
⌨️ () Routing - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Routing

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:52:07 - 00:59:08
⌨️ () Query Construction - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Query Construction

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
00:59:08 - 01:05:05
⌨️ () Indexing (Multi Representation) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Indexing (Multi Representation)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
01:05:05 - 01:11:39
⌨️ () Indexing (RAPTOR) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Indexing (RAPTOR)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
01:11:39 - 01:19:19
⌨️ () Indexing (ColBERT) - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Indexing (ColBERT)

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
01:19:19 - 01:26:32
⌨️ () CRAG - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () CRAG

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
01:26:32 - 01:44:09
⌨️ () Adaptive RAG - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Adaptive RAG

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
01:44:09 - 02:12:02
⌨️ () Is RAG Really Dead? - RAG From Scratch – Tutorial from LangChain Engineer

⌨️ () Is RAG Really Dead?

RAG From Scratch – Tutorial from LangChain Engineer
2024年04月17日 
02:12:02 - 02:33:11
⌨️ () Video Introduction - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Video Introduction

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:00:00 - 00:03:49
⌨️ () Introduction to Data Science and A/B Testing - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Introduction to Data Science and A/B Testing

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:03:49 - 00:05:38
⌨️ () Basics of A/B Testing in Data Science - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Basics of A/B Testing in Data Science

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:05:38 - 00:07:06
⌨️ () Key Parameters of A/B Testing for Data Scientists - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Key Parameters of A/B Testing for Data Scientists

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:07:06 - 00:09:24
⌨️ () Formulating Hypotheses and Identifying Primary Metrics in Data Science A/B Testing - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Formulating Hypotheses and Identifying Primary Metrics in Data Science A/B Testing

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:09:24 - 00:19:55
⌨️ () Designing an A/B Test: Data Science Approach - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Designing an A/B Test: Data Science Approach

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:19:55 - 00:37:56
⌨️ () Resources for A/B Testing in Data Science - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Resources for A/B Testing in Data Science

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:37:56 - 00:39:22
⌨️ () Analyzing A/B Test Results in Python: Data Science Techniques - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Analyzing A/B Test Results in Python: Data Science Techniques

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
00:39:22 - 01:01:00
⌨️ () Data Science Portfolio Project: Case Study with AB Testing - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Data Science Portfolio Project: Case Study with AB Testing

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:01:00 - 01:04:38
⌨️ () Reintroduction to A/B Testing in the Data Science Process - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Reintroduction to A/B Testing in the Data Science Process

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:04:38 - 01:21:07
⌨️ () Data Science Techniques: Loading Data with Pandas for A/B Testing - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Data Science Techniques: Loading Data with Pandas for A/B Testing

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:21:07 - 01:29:19
⌨️ () Data Science Visualization: Using Matplotlib and Seaborn for A/B Test Click Data - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Data Science Visualization: Using Matplotlib and Seaborn for A/B Test Click Data

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:29:19 - 01:38:38
⌨️ () Data Science Power Analysis: Understanding A/B Test Model Parameters - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Data Science Power Analysis: Understanding A/B Test Model Parameters

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:38:38 - 01:44:25
⌨️ () Data Science Calculations: Pooled Estimates and Variance for A/B Testing - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Data Science Calculations: Pooled Estimates and Variance for A/B Testing

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
01:44:25 - 02:06:48
⌨️ () Computing A/B Test P-Values: Data Science Methods for Statistical Significance - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Computing A/B Test P-Values: Data Science Methods for Statistical Significance

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
02:06:48 - 02:12:42
⌨️ () Practical Significance in A/B Testing: A Data Science Perspective - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Practical Significance in A/B Testing: A Data Science Perspective

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
02:12:42 - 02:29:07
⌨️ () Conclusion: Wrapping Up A/B Testing in Data Science - Data Science Essentials – Crash Course in A/B Testing with Case Study

⌨️ () Conclusion: Wrapping Up A/B Testing in Data Science

Data Science Essentials – Crash Course in A/B Testing with Case Study
2024年04月16日 
02:29:07 - 02:33:06
⌨️ () Introduction - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Introduction

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:00:00 - 00:01:21
⌨️ () Create account - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Create account

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:01:21 - 00:02:15
⌨️ () Create server - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Create server

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:02:15 - 00:07:53
⌨️ () Install software - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Install software

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:07:53 - 00:11:52
⌨️ () Configure Postgresql - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Configure Postgresql

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:11:52 - 00:15:56
⌨️ () Users and environment - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Users and environment

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:15:56 - 00:19:41
⌨️ () Requirements.txt - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Requirements.txt

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:19:41 - 00:22:26
⌨️ () Separate settings file - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Separate settings file

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:22:26 - 00:24:01
⌨️ () Introducing Git - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Introducing Git

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:24:01 - 00:31:36
⌨️ () Environmental variables - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Environmental variables

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:31:36 - 00:33:16
⌨️ () Init database - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Init database

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:33:16 - 00:36:46
⌨️ () Configure Gunicorn - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Configure Gunicorn

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:36:46 - 00:45:25
⌨️ () Configure Supervisor - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Configure Supervisor

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:45:25 - 00:48:44
⌨️ () Configure Nginx - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Configure Nginx

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:48:44 - 00:57:38
⌨️ () SSL / Let's Encrypt - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () SSL / Let's Encrypt

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:57:38 - 00:59:26
⌨️ () Repeat procedure - Digital Ocean Tutorial – Deploy Django and Other Frameworks

⌨️ () Repeat procedure

Digital Ocean Tutorial – Deploy Django and Other Frameworks
2024年04月15日 
00:59:26 - 01:15:47
⌨️ () Introduction - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Introduction

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:00:00 - 00:01:54
The timing on this video being dropped was PERFECT. I was JUST complaining there wasn't a good video on this 😂 She's brilliant can't wait to finish this. - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

The timing on this video being dropped was PERFECT. I was JUST complaining there wasn't a good video on this 😂 She's brilliant can't wait to finish this.

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日  @beemoore6578 様 
00:01:30 - 01:29:35
⌨️ () What is Figma? - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () What is Figma?

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:01:54 - 00:02:22
⌨️ () The design - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () The design

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:02:22 - 00:06:28
⌨️ () Locofy Lightning and LocoAI - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Locofy Lightning and LocoAI

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:06:28 - 00:25:18
Starting at  Ania is showing the responsiveness - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

Starting at Ania is showing the responsiveness

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日  @jando3176 様 
00:12:50 - 01:29:35
⌨️ () Let’s build out our app! - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Let’s build out our app!

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:25:18 - 00:40:45
⌨️ () Sync to GitHub - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Sync to GitHub

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:40:45 - 00:49:40
⌨️ () Create a Database - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Create a Database

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:49:40 - 00:54:49
⌨️ () Create Authentication - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Create Authentication

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
00:54:49 - 01:28:20
⌨️ () Let’s deploy our app! - One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI

⌨️ () Let’s deploy our app!

One-Click AI Web Development Tutorial - Learn how to Turn Figma Designs into Working Code using AI
2024年04月11日 
01:28:20 - 01:29:35
⌨️ () Intro - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Intro

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
00:00:00 - 00:01:30
⌨️ () AI Web App - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () AI Web App

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
00:01:30 - 03:07:35
Django - Learn Python Backend Development by Building 3 Projects [Full Course]

Django

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日  @jonathanmeza4141 様 
01:02:13 - 01:11:33
Postgres - Learn Python Backend Development by Building 3 Projects [Full Course]

Postgres

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日  @jonathanmeza4141 様 
01:11:33 - 10:08:02
@CodeWithTomi can you post the information on setting up the Qovery account with AWS you mentioned at timestamp ? Thanks! - Learn Python Backend Development by Building 3 Projects [Full Course]

@CodeWithTomi can you post the information on setting up the Qovery account with AWS you mentioned at timestamp ? Thanks!

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日  @Dorso2009 様 
01:13:20 - 10:08:02
I'm stuck on . i got "error 500" - Learn Python Backend Development by Building 3 Projects [Full Course]

I'm stuck on . i got "error 500"

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日  @walassi834 様 
02:33:00 - 10:08:02
⌨️ () Netflix Clone - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Netflix Clone

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
03:07:35 - 06:11:33
⌨️ () Spotify Clone - Part 1 - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Spotify Clone - Part 1

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
06:11:33 - 06:33:25
⌨️ () Spotify Clone - Part 2 - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Spotify Clone - Part 2

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
06:33:25 - 06:55:45
⌨️ () Spotify Clone - Part 3 - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Spotify Clone - Part 3

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
06:55:45 - 09:50:21
⌨️ () Spotify Clone - Part 4 - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Spotify Clone - Part 4

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
09:50:21 - 10:07:48
⌨️ () Outro - Learn Python Backend Development by Building 3 Projects [Full Course]

⌨️ () Outro

Learn Python Backend Development by Building 3 Projects [Full Course]
2024年04月10日 
10:07:48 - 10:08:02
⌨️ () Course Overview - Learn React Router v6 – Full Course

⌨️ () Course Overview

Learn React Router v6 – Full Course
2024年04月04日 
00:00:00 - 00:02:23
⌨️ () Introduction To React Router - Learn React Router v6 – Full Course

⌨️ () Introduction To React Router

Learn React Router v6 – Full Course
2024年04月04日 
00:02:23 - 00:05:08
⌨️ () Project Overview - Learn React Router v6 – Full Course

⌨️ () Project Overview

Learn React Router v6 – Full Course
2024年04月04日 
00:05:08 - 00:07:01
⌨️ () Project Setup - Learn React Router v6 – Full Course

⌨️ () Project Setup

Learn React Router v6 – Full Course
2024年04月04日 
00:07:01 - 00:09:23
⌨️ () Installing React Router - Learn React Router v6 – Full Course

⌨️ () Installing React Router

Learn React Router v6 – Full Course
2024年04月04日 
00:09:23 - 00:10:33
⌨️ () Setting up React Router - Learn React Router v6 – Full Course

⌨️ () Setting up React Router

Learn React Router v6 – Full Course
2024年04月04日 
00:10:33 - 00:14:11
⌨️ () Introduction to Routing - Learn React Router v6 – Full Course

⌨️ () Introduction to Routing

Learn React Router v6 – Full Course
2024年04月04日 
00:14:11 - 00:20:37
⌨️ () Boilerplate code - Learn React Router v6 – Full Course

⌨️ () Boilerplate code

Learn React Router v6 – Full Course
2024年04月04日 
00:20:37 - 00:21:23
⌨️ () Adding a new Route - Learn React Router v6 – Full Course

⌨️ () Adding a new Route

Learn React Router v6 – Full Course
2024年04月04日 
00:21:23 - 00:22:12
⌨️ () How to Navigate between Pages - Learn React Router v6 – Full Course

⌨️ () How to Navigate between Pages

Learn React Router v6 – Full Course
2024年04月04日 
00:22:12 - 00:25:01
⌨️ () Nested Routes - Learn React Router v6 – Full Course

⌨️ () Nested Routes

Learn React Router v6 – Full Course
2024年04月04日 
00:25:01 - 00:31:37
⌨️ () Creating a custom "Not Found" page - Learn React Router v6 – Full Course

⌨️ () Creating a custom "Not Found" page

Learn React Router v6 – Full Course
2024年04月04日 
00:31:37 - 00:35:30
⌨️ () Dynamic Routing - Learn React Router v6 – Full Course

⌨️ () Dynamic Routing

Learn React Router v6 – Full Course
2024年04月04日 
00:35:30 - 00:43:34
⌨️ () Programmatic Navigation - Learn React Router v6 – Full Course

⌨️ () Programmatic Navigation

Learn React Router v6 – Full Course
2024年04月04日 
00:43:34 - 00:53:27
⌨️ () Route Guarding - Learn React Router v6 – Full Course

⌨️ () Route Guarding

Learn React Router v6 – Full Course
2024年04月04日 
00:53:27 - 01:02:45
⌨️ () Navbar Adjustment - Learn React Router v6 – Full Course

⌨️ () Navbar Adjustment

Learn React Router v6 – Full Course
2024年04月04日 
01:02:45 - 01:06:07
⌨️ () Navigation Transition Animation - Learn React Router v6 – Full Course

⌨️ () Navigation Transition Animation

Learn React Router v6 – Full Course
2024年04月04日 
01:06:07 - 01:16:54
⌨️ () Lazy Loading - Learn React Router v6 – Full Course

⌨️ () Lazy Loading

Learn React Router v6 – Full Course
2024年04月04日 
01:16:54 - 01:24:34
⌨️ () Advanced Route Config - Learn React Router v6 – Full Course

⌨️ () Advanced Route Config

Learn React Router v6 – Full Course
2024年04月04日 
01:24:34 - 01:37:09
⌨️ () The Final Project - Learn React Router v6 – Full Course

⌨️ () The Final Project

Learn React Router v6 – Full Course
2024年04月04日 
01:37:09 - 01:38:09
⌨️ () The END! - Learn React Router v6 – Full Course

⌨️ () The END!

Learn React Router v6 – Full Course
2024年04月04日 
01:38:09 - 01:43:23
⌨️ () Intro - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Intro

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:00:00 - 00:03:35
⌨️ () Setup - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Setup

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:03:35 - 00:16:40
⌨️ () Loading assets - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Loading assets

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:16:40 - 00:19:36
⌨️ () How to use Tiled to draw maps - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () How to use Tiled to draw maps

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:19:36 - 00:36:23
⌨️ () Writing logic to display map - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Writing logic to display map

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:36:23 - 00:45:02
⌨️ () Creating the player - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Creating the player

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:45:02 - 00:52:13
⌨️ () Writing logic to display boundaries - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Writing logic to display boundaries

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:52:13 - 00:58:07
⌨️ () Writing logic to display dialogue - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Writing logic to display dialogue

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
00:58:07 - 01:16:28
⌨️ () Spawning the player + player movement logic - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Spawning the player + player movement logic

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
01:16:28 - 01:26:33
⌨️ () Writing logic for scaling the camera + animations + dialogue text - Build a Dev Portfolio as a 2D Game – JavaScript Course

⌨️ () Writing logic for scaling the camera + animations + dialogue text

Build a Dev Portfolio as a 2D Game – JavaScript Course
2024年04月04日 
01:26:33 - 01:37:41