- Category Classifier（01:36:37 - 01:39:14） - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Category Classifier（01:36:37 - 01:39:14）
Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

In this video we walk through a real world python machine learning project using the sci-kit learn library. In it we work our way to building a model that automatically classifies...
Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

In this video we walk through a real world python machine learning project using the sci-kit learn library. In it we work our way to building a model that automatically classifies text as either having a positive or negative sentiment. We do this by using amazon reviews as our training data. Full video timeline in the comments!

Link to Code & Data:
https://github.com/keithgalli/sklearn

Raw Data download:
http://jmcauley.ucsd.edu/data/amazon/

Sci-kit learn documentation:
https://scikit-learn.org/stable/documentation.html

Make sure you have sci-kit learn downloaded! To do this either run "pip install sklearn" or use python through Anaconda.

Join the Python Army to get access to perks!
YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join
Patreon - https://www.patreon.com/keithgalli

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Instagram: https://www.instagram.com/keithgalli/
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https://www.instagram.com/pagandvls/

---------------------------

Video outline!
0:00 - What we will be doing!
3:40 - Sci-Kit Learn Overview
6:38 - How do we find training data?
9:33 - Download data
11:45 - Load our data into Jupyter Notebook
16:38 - Cleaning our code a bit (building data class)
20:13 - Using Enums
22:50 - Converting text to numerical vectors, bag of words (BOW) explanation
25:45 - Training/Test Split (make sure to "pip install sklearn" !)
33:45 - Bag of words in sklearn (CountVectorizer)
40:05 - fit_transform, fit, transform methods
42:05 - Model Selection (SVM, Decision Tree, Naive Bayes, Logistic Regression) & Classification
47:50 - predict method
53:35 - Analysis & Evaluation (using clf.score() method)
56:58 - F1 score
1:01:01 - Improving our model (evenly distributing positive & negative examples and loading in more data)
1:20:36 - Let's see our model in action! (qualitative testing)
1:22:24 - Tfidf Vectorizer
1:25:40 - GridSearchCv to automatically find the best parameters
1:31:30 - Further NLP improvement opportunities
1:32:50 - Saving our model (Pickle) and reloading it later
1:36:37 - Category Classifier
1:39:14 - Confusion Matrix

---------------------
If you are curious to learn how I make my tutorials, check out this video: https://youtu.be/LEO4igyXbLs

*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

#Keith Galli #MIT #sklearn #python machine learning #nlp #machine learning project #artificial intelligence #sci kit learn #sci-kit learn #AI #python 3 #jupyter notebook #data science #ML #python data science #model selection #classification #regression #algorithms #sklearn overview #machine learning in python #python programming #programming #advanced #simple #complete #save model #confusion matrix #python plotting #sentiment #natural language processing #project #machine learning

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- What we will be doing! - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- What we will be doing!

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:00:20 - 00:03:40
i wonder what the outcome will be for sarcasm, something like: 'beautiful restaurant that made me puke, raccomand' - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

i wonder what the outcome will be for sarcasm, something like: 'beautiful restaurant that made me puke, raccomand'

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:01:05 - 01:40:49
- Sci-Kit Learn Overview - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Sci-Kit Learn Overview

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:03:40 - 00:06:38
- How do we find training data? - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- How do we find training data?

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:06:38 - 00:09:33
- Download data - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Download data

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:09:33 - 00:11:45
- Load our data into Jupyter Notebook - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Load our data into Jupyter Notebook

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:11:45 - 00:16:38
- Cleaning our code a bit (building data class) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Cleaning our code a bit (building data class)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:16:38 - 00:20:13
- Using Enums - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Using Enums

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:20:13 - 00:22:50
- Converting text to numerical vectors, bag of words (BOW) explanation - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Converting text to numerical vectors, bag of words (BOW) explanation

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:22:50 - 00:25:45
- Training/Test Split (make sure to "pip install sklearn" !) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Training/Test Split (make sure to "pip install sklearn" !)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:25:45 - 00:33:45
Hey Keith, I am facing an issue reproducing your code. On your video at , there is an object named training that you print as training[0]. It doesn’t work on my side, but I’m unable to understand the reason. It looks like the training[0] is not accessible, doesn’t exist, don’t know exactly what’s happening.. Do you know if something changed on train_test_split function or pandas dataframe since you published your tutorial? Thanks in advance. - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

Hey Keith, I am facing an issue reproducing your code. On your video at , there is an object named training that you print as training[0]. It doesn’t work on my side, but I’m unable to understand the reason. It looks like the training[0] is not accessible, doesn’t exist, don’t know exactly what’s happening.. Do you know if something changed on train_test_split function or pandas dataframe since you published your tutorial? Thanks in advance.

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:31:15 - 01:40:49
- Bag of words in sklearn (CountVectorizer) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Bag of words in sklearn (CountVectorizer)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:33:45 - 00:40:05
Bro, I didnt get why you used Train_X as vectorizer? at ? What is the actual reason as we have a huge dataset or 670 rows n hundreds of column :/ - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

Bro, I didnt get why you used Train_X as vectorizer? at ? What is the actual reason as we have a huge dataset or 670 rows n hundreds of column :/

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:38:53 - 01:40:49
- fit_transform, fit, transform methods - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- fit_transform, fit, transform methods

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:40:05 - 00:42:05
- Model Selection (SVM, Decision Tree, Naive Bayes, Logistic Regression) & Classification - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Model Selection (SVM, Decision Tree, Naive Bayes, Logistic Regression) & Classification

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:42:05 - 00:47:50
He's referring to Patrick Winston. By sheer chance I was watching one of his lectures on YT early this morning. - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

He's referring to Patrick Winston. By sheer chance I was watching one of his lectures on YT early this morning.

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:43:00 - 01:40:49
I am at the mark. - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

I am at the mark.

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:44:00 - 01:40:49
- predict method - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- predict method

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:47:50 - 00:53:35
- Analysis & Evaluation (using clf.score() method) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Analysis & Evaluation (using clf.score() method)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:53:35 - 00:56:58
- F1 score - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- F1 score

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
00:56:58 - 01:01:01
- Improving our model (evenly distributing positive & negative examples and loading in more data) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Improving our model (evenly distributing positive & negative examples and loading in more data)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:01:01 - 01:20:36
- Let's see our model in action! (qualitative testing) - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Let's see our model in action! (qualitative testing)

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:20:36 - 01:22:24
- Tfidf Vectorizer - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Tfidf Vectorizer

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:22:24 - 01:25:40
- GridSearchCv to automatically find the best parameters - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- GridSearchCv to automatically find the best parameters

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:25:40 - 01:31:30
- Further NLP improvement opportunities - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Further NLP improvement opportunities

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:31:30 - 01:32:50
- Saving our model (Pickle) and reloading it later - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Saving our model (Pickle) and reloading it later

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:32:50 - 01:36:37
- Category Classifier - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Category Classifier

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:36:37 - 01:39:14
- Confusion Matrix - Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)

- Confusion Matrix

Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc)
2019年10月01日　
01:39:14 - 01:40:49
チャンネル登録YouTube RSS

Keith Galli

※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。

概要 カレンダー 動画一覧 タイムテーブル チャンネル分析

Timetable

動画タイムテーブル

スペースでAND検索・ORで区切るとOR検索・先頭に「-」で除外検索

動画数：88件

- Livestream Overview - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Livestream Overview

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:00:00 - 00:04:00
- About the Olympics dataset (source website and how it was scraped) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- About the Olympics dataset (source website and how it was scraped)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:04:00 - 00:09:50
- Cleaning the dataset (getting started with code & data) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Cleaning the dataset (getting started with code & data)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:09:50 - 00:19:26
- What aspects of our data should be cleaned? - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- What aspects of our data should be cleaned?

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:19:26 - 00:29:08
- Get rid of bullet points in Used name column - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Get rid of bullet points in Used name column

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:29:08 - 00:34:08
- How to split Measurements into two separate height/weight numeric columns. - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- How to split Measurements into two separate height/weight numeric columns.

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
00:34:08 - 01:05:00
- Parse out dates from Born & Died columns - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Parse out dates from Born & Died columns

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
01:05:00 - 01:25:43
- Parse out city, region, and country from Born column (working with regular expressions) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Parse out city, region, and country from Born column (working with regular expressions)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
01:25:43 - 01:41:15
- Get rid of the extra columns - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Get rid of the extra columns

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
01:41:15 - 01:46:08
- Next steps (how would we clean the results.csv) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Next steps (how would we clean the results.csv)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
01:46:08 - 01:49:41
- Questions & Answers - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Questions & Answers

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日　
01:49:41 - 02:02:23
- Intro & Setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Intro & Setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:00:00 - 00:02:14
great video! however, regarding the usage of the terminal to create directories etc at , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :) - Solving 100 Python Pandas Problems! (from easy to very difficult)

great video! however, regarding the usage of the terminal to create directories etc at , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :)

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　 @realzeejay 様　
00:00:59 - 05:20:18
- Problems (1-3) Initial pandas setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (1-3) Initial pandas setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:02:14 - 00:04:42
- Problems (4-10) DataFrame operations - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (4-10) DataFrame operations

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:04:42 - 00:04:52
- 4) Create a dataframe from dictionary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 4) Create a dataframe from dictionary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:04:52 - 00:05:24
- 5) Display dataframe summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 5) Display dataframe summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:05:24 - 00:05:41
- 6) First 3 rows of the dataframe - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 6) First 3 rows of the dataframe

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:05:41 - 00:06:02
- 7) Select ‘animal’ and ‘age’ columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 7) Select ‘animal’ and ‘age’ columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:06:02 - 00:07:42
- 8) Data in specific rows and columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 8) Data in specific rows and columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:07:42 - 00:09:06
- 9) Rows with visits greater than 3 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 9) Rows with visits greater than 3

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:09:06 - 00:09:57
- 10) Rows with NaN in age - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 10) Rows with NaN in age

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:09:57 - 00:10:56
- 11) Cats younger than 3 years - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 11) Cats younger than 3 years

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:10:56 - 00:11:35
- 12) Age between 2 and 4 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 12) Age between 2 and 4

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:11:35 - 00:12:45
- 13) Change age in row ‘f’ - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 13) Change age in row ‘f’

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:12:45 - 00:15:56
- 14) Sum of all visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 14) Sum of all visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:15:56 - 00:16:41
- 15) Average age by animal - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 15) Average age by animal

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:16:41 - 00:20:21
I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”}) - Solving 100 Python Pandas Problems! (from easy to very difficult)

I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”})

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　 @AgustinGonzalez-tz3yr 様　
00:19:30 - 05:20:18
- 16) Modify and revert rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 16) Modify and revert rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:20:21 - 00:24:06
- 17) Count by animal type - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 17) Count by animal type

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:24:06 - 00:25:28
- Quick review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Quick review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:25:28 - 00:26:17
- 18) Sort by age and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 18) Sort by age and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:26:17 - 00:28:07
- 19) Convert 'priority' to boolean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 19) Convert 'priority' to boolean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:28:07 - 00:29:42
- 20) Replace 'snake' with 'python' - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 20) Replace 'snake' with 'python'

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:29:42 - 00:30:53
- 21) Mean age by animal and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 21) Mean age by animal and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:30:53 - 00:33:49
- Advanced DataFrame techniques - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Advanced DataFrame techniques

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:33:49 - 00:33:57
- 22) Filter duplicate integers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 22) Filter duplicate integers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:33:57 - 00:43:18
- 23) Subtract row mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 23) Subtract row mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:43:18 - 00:45:42
- 24) Column with smallest sum - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 24) Column with smallest sum

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:45:42 - 00:50:39
- 25) Count unique rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 25) Count unique rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:50:39 - 00:53:17
- 26) Column with third NaN - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 26) Column with third NaN

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
00:53:17 - 01:10:27
- Solution review for 26 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review for 26

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:10:27 - 01:17:13
- 27) Sum of top three values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 27) Sum of top three values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:17:13 - 01:24:01
- 28) Sum by column condition - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 28) Sum by column condition

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:24:01 - 01:40:11
- Recent problem review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Recent problem review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:40:11 - 01:42:53
- 29) Count differences since last zero - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 29) Count differences since last zero

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:42:53 - 01:56:19
- 30) Locate largest values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 30) Locate largest values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
01:56:19 - 02:08:38
- 31) Replace negatives with mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 31) Replace negatives with mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:08:38 - 02:17:43
- 32) Rolling mean over groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 32) Rolling mean over groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:17:43 - 02:23:10
- Series and DatetimeIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Series and DatetimeIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:23:10 - 02:23:12
- 33) DatetimeIndex for 2015 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 33) DatetimeIndex for 2015

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:23:12 - 02:27:56
- 34) Sum values on Wednesdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 34) Sum values on Wednesdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:27:56 - 02:45:04
- 35) Monthly mean values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 35) Monthly mean values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:45:04 - 02:46:16
- 36) Best value in four-month groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 36) Best value in four-month groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:46:16 - 02:50:26
- 37) DatetimeIndex of third Thursdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 37) DatetimeIndex of third Thursdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:50:26 - 02:59:03
- Cleaning Data - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Cleaning Data

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:59:03 - 02:59:40
- 38) Fill missing FlightNumber - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 38) Fill missing FlightNumber

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
02:59:40 - 03:02:45
- 39) Split column by delimiter - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 39) Split column by delimiter

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:02:45 - 03:06:47
- 40) Fix city name capitalization - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 40) Fix city name capitalization

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:06:47 - 03:08:30
- 41) Reattach columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 41) Reattach columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:08:30 - 03:13:11
- 42) Fix airline name punctuation - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 42) Fix airline name punctuation

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:13:11 - 03:17:45
- 43) Expand RecentDelays into columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 43) Expand RecentDelays into columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:17:45 - 03:27:31
- MultiIndexes in Pandas - Solving 100 Python Pandas Problems! (from easy to very difficult)

- MultiIndexes in Pandas

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:27:31 - 03:27:34
- 44) Construct a MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 44) Construct a MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:27:34 - 03:30:37
- Solution review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:30:37 - 03:32:44
- 45) Lexicographically sorted check - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 45) Lexicographically sorted check

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:32:44 - 03:32:58
- 46) Select specific MultiIndex labels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 46) Select specific MultiIndex labels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:32:58 - 03:34:23
- 47) Slice Series with MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 47) Slice Series with MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:34:23 - 03:35:24
- 48) Sum by first level - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 48) Sum by first level

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:35:24 - 03:37:47
- 49) Alternative sum method - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 49) Alternative sum method

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:37:47 - 03:40:08
- Additional solution insights - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Additional solution insights

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:40:08 - 03:41:22
- 50) Swap MultiIndex levels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 50) Swap MultiIndex levels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:41:22 - 03:45:27
- Minesweeper problems - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Minesweeper problems

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:45:27 - 03:45:44
- 51) Generate coordinate grid - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 51) Generate coordinate grid

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
03:45:44 - 04:00:28
- 52) Add 'safe' or 'mine' column - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 52) Add 'safe' or 'mine' column

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:00:28 - 04:03:04
- 53) Count adjacent mines - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 53) Count adjacent mines

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:03:04 - 04:27:33
- Review solution to 53 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Review solution to 53

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:27:33 - 04:33:02
- Skipped problems 54 & 55 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Skipped problems 54 & 55

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:33:02 - 04:33:11
- Plotting - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Plotting

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:33:11 - 04:33:12
- 56) Scatter plot with black x markers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 56) Scatter plot with black x markers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:33:12 - 04:41:26
- 57) Plot four data types - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 57) Plot four data types

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:41:26 - 04:52:50
- 58) Overlay multiple graphs - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 58) Overlay multiple graphs

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
04:52:50 - 05:03:11
- 59) Hourly stock data summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 59) Hourly stock data summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
05:03:11 - 05:14:12
- 60) Candlestick plot - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 60) Candlestick plot

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日　
05:14:12 - 05:20:18
- Intro & Live Stream Overview - Ask me anything! (data science, LLMs, landing a job, and more)

- Intro & Live Stream Overview

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:00:00 - 00:04:58
- How over saturated is the data science job market and will things improve in your opinion? - Ask me anything! (data science, LLMs, landing a job, and more)

- How over saturated is the data science job market and will things improve in your opinion?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:04:58 - 00:07:26
- How much maths is needed to get a data science job? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much maths is needed to get a data science job?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:07:26 - 00:09:55
- Can you share a basic roadmap to learn generative AI and LLMs? - Ask me anything! (data science, LLMs, landing a job, and more)

- Can you share a basic roadmap to learn generative AI and LLMs?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:09:55 - 00:13:08
- What future-proof tech career to should someone focus on who’s looking to change career? - Ask me anything! (data science, LLMs, landing a job, and more)

- What future-proof tech career to should someone focus on who’s looking to change career?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:13:08 - 00:16:52
- Is data structures & algorithms (dsa) necessary to get a job in data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is data structures & algorithms (dsa) necessary to get a job in data science?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:16:52 - 00:19:17
- How to get good at data structures and algorithms? - Ask me anything! (data science, LLMs, landing a job, and more)

- How to get good at data structures and algorithms?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:19:17 - 00:22:20
- Why don’t you make videos regularly now? - Ask me anything! (data science, LLMs, landing a job, and more)

- Why don’t you make videos regularly now?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:22:20 - 00:24:18
- How much do you need to know for entry-level roles / college internships? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much do you need to know for entry-level roles / college internships?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:24:18 - 00:27:02
- How important is domain knowledge for data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- How important is domain knowledge for data science?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:27:02 - 00:29:29
- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts - Ask me anything! (data science, LLMs, landing a job, and more)

- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:29:29 - 00:32:30
- Any good data projects to increase visibility to companies? - Ask me anything! (data science, LLMs, landing a job, and more)

- Any good data projects to increase visibility to companies?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:32:30 - 00:36:05
- Do you think we should all learn vector databases? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do you think we should all learn vector databases?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:36:05 - 00:39:10
- Is webscraping illegal? what can I do and not do? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is webscraping illegal? what can I do and not do?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:39:10 - 00:43:14
- What are you working on at the moment? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are you working on at the moment?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:43:14 - 00:45:25
- How can I turn a financial database I’m building into an interesting portfolio project to showcase work? - Ask me anything! (data science, LLMs, landing a job, and more)

- How can I turn a financial database I’m building into an interesting portfolio project to showcase work?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:45:25 - 00:49:23
- What advice do you have for data scientists who want to get into freelance/consulting? - Ask me anything! (data science, LLMs, landing a job, and more)

- What advice do you have for data scientists who want to get into freelance/consulting?

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2024年04月07日　
00:49:23 - 00:55:15
- What are important skills for DS beyond ML & AI? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are important skills for DS beyond ML & AI?

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2024年04月07日　
00:55:15 - 00:59:42
- Do I need to become a full-stack programmer to have success in this field? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do I need to become a full-stack programmer to have success in this field?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
00:59:42 - 01:02:31
- If you weren’t allowed to do programming or create content, what would you do? - Ask me anything! (data science, LLMs, landing a job, and more)

- If you weren’t allowed to do programming or create content, what would you do?

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2024年04月07日　
01:02:31 - 01:03:39
- How did you achieve your advanced height? Asking for a friend. - Ask me anything! (data science, LLMs, landing a job, and more)

- How did you achieve your advanced height? Asking for a friend.

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2024年04月07日　
01:03:39 - 01:04:23
- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links. - Ask me anything! (data science, LLMs, landing a job, and more)

- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日　
01:04:23 - 01:05:26
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