- Python Machine Learning Tutorial #2 - Linear Regression p.1

Python Machine Learning Tutorial #2 - Linear Regression p.1

In this python machine learning tutorial I will be introducing you to linear regression and data collection and trimming. Data is by far the most important part of any machine learning project and therefore it is very important that we determine which data is important and will have an influence ...
In this python machine learning tutorial I will be introducing you to linear regression and data collection and trimming. Data is by far the most important part of any machine learning project and therefore it is very important that we determine which data is important and will have an influence on our final prediction.

⭐ Kite is a free AI-powered coding assistant for Python that will help you code smarter and faster. Integrates with Atom, PyCharm, VS Code, Sublime, Vim, and Spyder. I've been using Kite for 6 months and I love it! https://kite.com/download/?utm_medium=referral&utm_source=youtube&utm_campaign=techwithtim&utm_content=description-only

To have access to all resources and code seen in future videos visit my website!

WEBISTE: https://techwithtim.net/tutorials/machine-learning-python/linear-regression/

UCI Data Set: https://archive.ics.uci.edu/ml/datasets/Student+Performance

**************************************************************
proXPN VPN: https://secure.proxpn.com/?a_aid=5c34b30d44d9d
Use the Code "SAVE6144" For 50% Off!

One-Time Donations: https://goo.gl/pbCE9J

Support the Channel: https://www.patreon.com/techwithtim

Twitter: https://twitter.com/TechWithTimm

Join my discord server: https://discord.gg/pr2k55t
**************************************************************

Please leave a LIKE and SUBSCRIBE for more content!

Tags:
- Tech With Tim
- Machine learning with python
- Python machine learning for beginners
- Beginner machine learning tutorial python
- Machine learning tutorial 2019
- Python Tutorials
- Machine learning python

#tech with tim #python tutorials #python machine learning #python linear regression #linear regression machine learning #machine learning python beginner #machine learning linear regression python #machine learning linear regression #artificial intelligence #linear regression
imports in test.py were tensorflow and keras, none of which are present at - Python Machine Learning Tutorial #2 - Linear Regression p.1

imports in test.py were tensorflow and keras, none of which are present at

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:04:35 - 00:14:55
can you please show the configuration at - Python Machine Learning Tutorial #2 - Linear Regression p.1

can you please show the configuration at

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:40 - 00:14:55
hey man great tutorials. Please show us how you did your configuration at -8:43. Thanks. I think that is the reason why my data doesn't show up on the terminal. - Python Machine Learning Tutorial #2 - Linear Regression p.1

hey man great tutorials. Please show us how you did your configuration at -8:43. Thanks. I think that is the reason why my data doesn't show up on the terminal.

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:41 - 00:14:55
Question: When I printed the code at  I only get process finished with exit code 0 rather than what you had. Am I doing something wrong? - Python Machine Learning Tutorial #2 - Linear Regression p.1

Question: When I printed the code at I only get process finished with exit code 0 rather than what you had. Am I doing something wrong?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:42 - 00:14:55
Mozes mi pomoci ja kad pokusam pokrenuti kod na  izbaci error:/home/petar/anaconda3/envs/testproject1/bin/python: can't find '__main__' module in '/home/petar/PycharmProjects/testproject1' - Python Machine Learning Tutorial #2 - Linear Regression p.1

Mozes mi pomoci ja kad pokusam pokrenuti kod na izbaci error:/home/petar/anaconda3/envs/testproject1/bin/python: can't find '__main__' module in '/home/petar/PycharmProjects/testproject1'

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:43 - 00:14:55
here  ? - Python Machine Learning Tutorial #2 - Linear Regression p.1

here ?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:11:20 - 00:14:55
does that randomly sample 10% of the dat set, randomly sample with replacement, etc.? - Python Machine Learning Tutorial #2 - Linear Regression p.1

does that randomly sample 10% of the dat set, randomly sample with replacement, etc.?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:12:30 - 00:14:55
Great series! Really enjoyed the explanation at  for test data - Python Machine Learning Tutorial #2 - Linear Regression p.1

Great series! Really enjoyed the explanation at for test data

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:08 - 00:14:55
I would have loved to train on the testing data back in school ;) - Python Machine Learning Tutorial #2 - Linear Regression p.1

I would have loved to train on the testing data back in school ;)

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:24 - 00:14:55
fromI'm kind of confused. So what he's saying is,  we gonna give input as 10% of the data,  because our purpose is training, not  in order to store the data or create which is not based on machine learning. Am I getting right? - Python Machine Learning Tutorial #2 - Linear Regression p.1

fromI'm kind of confused. So what he's saying is, we gonna give input as 10% of the data, because our purpose is training, not in order to store the data or create which is not based on machine learning. Am I getting right?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:41 - 00:14:55
Tech With Tim

Tech With Tim

🎉 1,000,000 人達成! 🎉

【予測】200万人まであと644日(2024年7月9日)

チャンネル登録 RSS
Learn programming, software engineering, machine learning and everything tech from this channel. With a special emphasis on python and javascript my channel aims to give you free resources so that you can learn to code and dive into the software engineering and programming industry. My goal is to...
Learn programming, software engineering, machine learning and everything tech from this channel. With a special emphasis on python and javascript my channel aims to give you free resources so that you can learn to code and dive into the software engineering and programming industry. My goal is to provide the highest quality programming and tech videos on the internet!

Timetable

動画タイムテーブル

動画数:11件

probably should have spend a lot of time to figure out the " taregt" :-D  . BTW thanks tim for providing this kind of valuable video ❤️ - Python Machine Learning Tutorial #12 - Implementing K-Means Clustering

probably should have spend a lot of time to figure out the " taregt" :-D . BTW thanks tim for providing this kind of valuable video ❤️

Python Machine Learning Tutorial #12 - Implementing K-Means Clustering
2019年01月28日
00:10:49 - 00:12:34
you can see at lower right side that red area denotes 4,  and brown 9........ - Python Machine Learning Tutorial #11 - How K Means Clustering Works

you can see at lower right side that red area denotes 4, and brown 9........

Python Machine Learning Tutorial #11 - How K Means Clustering Works
2019年01月27日
00:02:04 - 00:13:47
Where's Wally? - Python Machine Learning Tutorial #11 - How K Means Clustering Works

Where's Wally?

Python Machine Learning Tutorial #11 - How K Means Clustering Works
2019年01月27日
00:08:36 - 00:13:47
yes I am also here and plz man upload more videos i am so lucky to watch these videos but i guess you stop this series... - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

yes I am also here and plz man upload more videos i am so lucky to watch these videos but i guess you stop this series...

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:00:30 - 00:10:05
yes I am still here... and PLZ PLZ add more videos to this series - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

yes I am still here... and PLZ PLZ add more videos to this series

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:00:30 - 00:10:05
I got 0.8859 xD don't see the problem lol and 2nd try 0.9122 - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

I got 0.8859 xD don't see the problem lol and 2nd try 0.9122

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:03:31 - 00:10:05
at , I got 10 times in a row ~0.9I also got no warning - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

at , I got 10 times in a row ~0.9I also got no warning

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:03:37 - 00:10:05
holy crap i got the exact same number as u ...or is getting similar accuracies common with a kernel? - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

holy crap i got the exact same number as u ...or is getting similar accuracies common with a kernel?

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:04:45 - 00:10:05
lmao love you Tim xP haha @ - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

lmao love you Tim xP haha @

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:06:38 - 00:10:05
Cool video! At min  Tim says that unsupervised learning is "like the stuff neural networks do". But I thought neural networks are always supervised (you have to provide the labels). Am I wrong? Can you provide me with some examples/neural network techniques that are unsupervised? - Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM

Cool video! At min Tim says that unsupervised learning is "like the stuff neural networks do". But I thought neural networks are always supervised (you have to provide the labels). Am I wrong? Can you provide me with some examples/neural network techniques that are unsupervised?

Python Machine Learning Tutorial #10 - SVM P.3 - Implementing a SVM
2019年01月26日
00:09:20 - 00:10:05
D plot , shouldnt x2 and x3 be switched?Btw good job on the lessons, helped me a lot. - Python Machine Learning Tutorial #9 - SVM P.2 - How Support Vector Machines Work

D plot , shouldnt x2 and x3 be switched?Btw good job on the lessons, helped me a lot.

Python Machine Learning Tutorial #9 - SVM P.2 - How Support Vector Machines Work
2019年01月25日
00:08:10 - 00:14:21
I think at  x3 and x2 are inverted, no ? - Python Machine Learning Tutorial #9 - SVM P.2 - How Support Vector Machines Work

I think at x3 and x2 are inverted, no ?

Python Machine Learning Tutorial #9 - SVM P.2 - How Support Vector Machines Work
2019年01月25日
00:09:00 - 00:14:21
I am getting the following error at  (min:sec) during Tutorial #7 videoprint("Predicted: ", names[predicted[x]], "Data: ", x_test[x], "Actual: ", names[y_test[x]])IndexError: list index out of rangeCan you shed some light as how to address this error? Thanks. - Python Machine Learning Tutorial #7 - KNN p.3 - Implementation

I am getting the following error at (min:sec) during Tutorial #7 videoprint("Predicted: ", names[predicted[x]], "Data: ", x_test[x], "Actual: ", names[y_test[x]])IndexError: list index out of rangeCan you shed some light as how to address this error? Thanks.

Python Machine Learning Tutorial #7 - KNN p.3 - Implementation
2019年01月23日
00:06:50 - 00:11:09
but i am color blind bro :( - Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?

but i am color blind bro :(

Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?
2019年01月22日
00:01:11 - 00:13:45
TECH WITH TIM! You said "a odd number" INSTEAD OF "an odd number." - Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?

TECH WITH TIM! You said "a odd number" INSTEAD OF "an odd number."

Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?
2019年01月22日
00:05:34 - 00:13:45
What about you get the 5 nearest neighbours to be 2 greens, 2 blues and 1 red?You can also have a tie in terms of distance if the data uses enough big units, and so you have no nearest point but rather nearest two points for example. - Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?

What about you get the 5 nearest neighbours to be 2 greens, 2 blues and 1 red?You can also have a tie in terms of distance if the data uses enough big units, and so you have no nearest point but rather nearest two points for example.

Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?
2019年01月22日
00:05:45 - 00:13:45
You've got a slight (albeit very important) mistake at about . You have to weigh the distances, not enumerate them. - Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?

You've got a slight (albeit very important) mistake at about . You have to weigh the distances, not enumerate them.

Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?
2019年01月22日
00:06:00 - 00:13:45
Wouldn't a KNN working with percentages solve this problem? - Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?

Wouldn't a KNN working with percentages solve this problem?

Python Machine Learning Tutorial #6 - KNN p.2 - How does K Nearest Neighbors Work?
2019年01月22日
00:10:58 - 00:13:45
- you said data se x not data sets - Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data

- you said data se x not data sets

Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data
2019年01月21日
00:01:38 - 00:12:55
at   I think you can right click on emply space on coding workspace and select run 'filename'   i think right click is easier option - Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data

at I think you can right click on emply space on coding workspace and select run 'filename' i think right click is easier option

Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data
2019年01月21日
00:04:58 - 00:12:55
Shouldn't be the values of the buying-list () be in range from 3 to 0 or 4 to 1 instead of 3 to 1? Because "very high", "high", "med" and "low" are four attributes. - Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data

Shouldn't be the values of the buying-list () be in range from 3 to 0 or 4 to 1 instead of 3 to 1? Because "very high", "high", "med" and "low" are four attributes.

Python Machine Learning Tutorial #5 - KNN p.1 - Irregular Data
2019年01月21日
00:09:55 - 00:12:55
please help with hotkeys for this action - Python Machine Learning Tutorial #4 - Saving Models & Plotting Data

please help with hotkeys for this action

Python Machine Learning Tutorial #4 - Saving Models & Plotting Data
2019年01月20日
00:06:28 - 00:13:43
Wouldn't it be more convenient just just to train the model and then if the accuracy was over 95 then writing the file? - Python Machine Learning Tutorial #4 - Saving Models & Plotting Data

Wouldn't it be more convenient just just to train the model and then if the accuracy was over 95 then writing the file?

Python Machine Learning Tutorial #4 - Saving Models & Plotting Data
2019年01月20日
00:07:18 - 00:13:43
I'm sorry, a little bit late but could you explain why you did that at ?  Thanks! - Python Machine Learning Tutorial #4 - Saving Models & Plotting Data

I'm sorry, a little bit late but could you explain why you did that at ? Thanks!

Python Machine Learning Tutorial #4 - Saving Models & Plotting Data
2019年01月20日
00:07:27 - 00:13:43
Is there a way for us to confirm that the model we saved at  has the highest accuracy? best is just equal to zero... then we don't change the best value anymore... so as soon as accuracy is bigger than 0 it will save the model... hummm.. - Python Machine Learning Tutorial #4 - Saving Models & Plotting Data

Is there a way for us to confirm that the model we saved at has the highest accuracy? best is just equal to zero... then we don't change the best value anymore... so as soon as accuracy is bigger than 0 it will save the model... hummm..

Python Machine Learning Tutorial #4 - Saving Models & Plotting Data
2019年01月20日
00:08:50 - 00:13:43
At  and I'm getting aNameError: name 'style' is not defined - Python Machine Learning Tutorial #4 - Saving Models & Plotting Data

At and I'm getting aNameError: name 'style' is not defined

Python Machine Learning Tutorial #4 - Saving Models & Plotting Data
2019年01月20日
00:10:43 - 00:13:43
In Singaporean Maths,  is covered in 7th Grade. - Python Machine Learning Tutorial #3 - Linear Regression p.2

In Singaporean Maths, is covered in 7th Grade.

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:03:42 - 00:17:06
I learnt it as y = mx + c - Python Machine Learning Tutorial #3 - Linear Regression p.2

I learnt it as y = mx + c

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:03:48 - 00:17:06
gradient - Python Machine Learning Tutorial #3 - Linear Regression p.2

gradient

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:04:19 - 00:17:06
I don't know if  is correct. It should be predicting a linear map from two variables to one, since we predict a third value based of any two values. The issue is that the line would only make predictions for a subset of the two values used to predict. Not trying to be pedantic, just not sure if I am understanding correctly - Python Machine Learning Tutorial #3 - Linear Regression p.2

I don't know if is correct. It should be predicting a linear map from two variables to one, since we predict a third value based of any two values. The issue is that the line would only make predictions for a subset of the two values used to predict. Not trying to be pedantic, just not sure if I am understanding correctly

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:07:02 - 00:17:06
One question: In  you noticed that you made a slight mistake, and as a result, you swapped y_train with x_test. How did you understand that it's a case to swapped those two? In other words, what was your logic to figure it out from the error message? BTW. doing tutorials with mistakes is cool, I see it more beneficial than having a clean tutorial without mistakes and without explaining those mistakes. - Python Machine Learning Tutorial #3 - Linear Regression p.2

One question: In you noticed that you made a slight mistake, and as a result, you swapped y_train with x_test. How did you understand that it's a case to swapped those two? In other words, what was your logic to figure it out from the error message? BTW. doing tutorials with mistakes is cool, I see it more beneficial than having a clean tutorial without mistakes and without explaining those mistakes.

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:09:39 - 00:17:06
Does anyone know why at  Tim swaps the x_test and y_train variables??? Or more specifically why his original code produces the error? - Python Machine Learning Tutorial #3 - Linear Regression p.2

Does anyone know why at Tim swaps the x_test and y_train variables??? Or more specifically why his original code produces the error?

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:09:52 - 00:17:06
small question:  if I try to run the program from , it keeps giving the error: - Python Machine Learning Tutorial #3 - Linear Regression p.2

small question: if I try to run the program from , it keeps giving the error:

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:09:55 - 00:17:06
I'm using a different file from UCI and at  I'm getting this error: TypeError: fit() missing 1 required positional argument: 'y'. Anyone knows what this might indicate? Maybe my dataset doesn't have labels for Y attributes? - Python Machine Learning Tutorial #3 - Linear Regression p.2

I'm using a different file from UCI and at I'm getting this error: TypeError: fit() missing 1 required positional argument: 'y'. Anyone knows what this might indicate? Maybe my dataset doesn't have labels for Y attributes?

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:09:56 - 00:17:06
I got 0.81 XD - Python Machine Learning Tutorial #3 - Linear Regression p.2

I got 0.81 XD

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:10:03 - 00:17:06
is the 'acc' variable supposed to output different values? that's what's happening for me - Python Machine Learning Tutorial #3 - Linear Regression p.2

is the 'acc' variable supposed to output different values? that's what's happening for me

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:10:30 - 00:17:06
at  where the coeffiecients are prented, why are there 5 of them? what are those 5 variables? - Python Machine Learning Tutorial #3 - Linear Regression p.2

at where the coeffiecients are prented, why are there 5 of them? what are those 5 variables?

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:11:55 - 00:17:06
At  , a line in 6 dimentional space would need 5 coef, just like in 2 dimentional space only 1 coef is needed. - Python Machine Learning Tutorial #3 - Linear Regression p.2

At , a line in 6 dimentional space would need 5 coef, just like in 2 dimentional space only 1 coef is needed.

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:12:28 - 00:17:06
: I think it's a 6-dimensional space as a 2-dimensional space function depends of 1 coefficient, not 2. - Python Machine Learning Tutorial #3 - Linear Regression p.2

: I think it's a 6-dimensional space as a 2-dimensional space function depends of 1 coefficient, not 2.

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:12:30 - 00:17:06
).  at . But gr8 video anyway :-) - Python Machine Learning Tutorial #3 - Linear Regression p.2

). at . But gr8 video anyway :-)

Python Machine Learning Tutorial #3 - Linear Regression p.2
2019年01月19日
00:14:12 - 00:17:06
imports in test.py were tensorflow and keras, none of which are present at - Python Machine Learning Tutorial #2 - Linear Regression p.1

imports in test.py were tensorflow and keras, none of which are present at

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:04:35 - 00:14:55
can you please show the configuration at - Python Machine Learning Tutorial #2 - Linear Regression p.1

can you please show the configuration at

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:40 - 00:14:55
hey man great tutorials. Please show us how you did your configuration at -8:43. Thanks. I think that is the reason why my data doesn't show up on the terminal. - Python Machine Learning Tutorial #2 - Linear Regression p.1

hey man great tutorials. Please show us how you did your configuration at -8:43. Thanks. I think that is the reason why my data doesn't show up on the terminal.

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:41 - 00:14:55
Question: When I printed the code at  I only get process finished with exit code 0 rather than what you had. Am I doing something wrong? - Python Machine Learning Tutorial #2 - Linear Regression p.1

Question: When I printed the code at I only get process finished with exit code 0 rather than what you had. Am I doing something wrong?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:42 - 00:14:55
Mozes mi pomoci ja kad pokusam pokrenuti kod na  izbaci error:/home/petar/anaconda3/envs/testproject1/bin/python: can't find '__main__' module in '/home/petar/PycharmProjects/testproject1' - Python Machine Learning Tutorial #2 - Linear Regression p.1

Mozes mi pomoci ja kad pokusam pokrenuti kod na izbaci error:/home/petar/anaconda3/envs/testproject1/bin/python: can't find '__main__' module in '/home/petar/PycharmProjects/testproject1'

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:08:43 - 00:14:55
here  ? - Python Machine Learning Tutorial #2 - Linear Regression p.1

here ?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:11:20 - 00:14:55
does that randomly sample 10% of the dat set, randomly sample with replacement, etc.? - Python Machine Learning Tutorial #2 - Linear Regression p.1

does that randomly sample 10% of the dat set, randomly sample with replacement, etc.?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:12:30 - 00:14:55
Great series! Really enjoyed the explanation at  for test data - Python Machine Learning Tutorial #2 - Linear Regression p.1

Great series! Really enjoyed the explanation at for test data

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:08 - 00:14:55
I would have loved to train on the testing data back in school ;) - Python Machine Learning Tutorial #2 - Linear Regression p.1

I would have loved to train on the testing data back in school ;)

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:24 - 00:14:55
fromI'm kind of confused. So what he's saying is,  we gonna give input as 10% of the data,  because our purpose is training, not  in order to store the data or create which is not based on machine learning. Am I getting right? - Python Machine Learning Tutorial #2 - Linear Regression p.1

fromI'm kind of confused. So what he's saying is, we gonna give input as 10% of the data, because our purpose is training, not in order to store the data or create which is not based on machine learning. Am I getting right?

Python Machine Learning Tutorial #2 - Linear Regression p.1
2019年01月18日
00:13:41 - 00:14:55