Data Science from Scratch

This is a fork with executed code of the book Data Science from Scratch written by Joel Grus. All examples are made as .ipynb files in Jupiter Notebook.

I created executable files while studying this book. All files partially repeat the code from the book, but a part of the code is changed, updated and adapted to Python 3.

I used russian edition of the first edition of original book. First edition was originally published in 2015 and there was a second edition in 2019. So part of the code has been significantly updated by me.

Table of Contents

1. Introduction
2. A Crash Course in Python
3. Visualizing Data
4. Linear Algebra
5. Statistics
6. Probability
7. Hypothesis and Inference
8. Gradient Descent
9. Getting Data
10. Working With Data
11. Machine Learning
12. k-Nearest Neighbors
13. Naive Bayes
14. Simple Linear Regression
15. Multiple Regression
16. Logistic Regression
17. Decision Trees
18. Neural Networks
19. Clustering
20. Natural Language Processing
21. Network Analysis
22. Recommender Systems
23. Databases and SQL
24. MapReduce
25. Go Forth And Do Data Science