https://github.com/brpy/ml-books

A list of freely available Machine Learning related books.
https://github.com/brpy/ml-books

books data-science free freely machine-learning statistics

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A list of freely available Machine Learning related books.

• Host: GitHub
• URL: https://github.com/brpy/ml-books
• Owner: brpy
• License: mit
• Created: 2020-05-11T06:28:57.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-12-31T20:13:01.000Z (almost 4 years ago)
• Last Synced: 2024-11-05T10:12:06.956Z (about 2 months ago)
• Topics: books, data-science, free, freely, machine-learning, statistics
• Homepage:
• Size: 5.86 KB
• Stars: 23
• Watchers: 2
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ml-books

A list of freely available Machine Learning, Data Science and Statistics books.

| Book/Resource| Author(s) | Links|:arrow_double_down:|

|-----------|----------------------------|-----------------------------------------------|---|

| d2l-ai| Community | [[github]](https://github.com/d2l-ai/d2l-en) [[pdf]](https://d2l.ai/d2l-en.pdf)|:heavy_check_mark:|

| Data Science Handbook|  Jake Vanderplas | [[github]](https://github.com/jakevdp/PythonDataScienceHandbook) [[online]](https://jakevdp.github.io/PythonDataScienceHandbook/)|:x:|

| Deep Learning Book| Ian Goodfellow, Yoshua Bengio, Aaron Courville | [[online]](https://www.deeplearningbook.org/)|:x:|

| Deep Learning with Pytorch|Eli Stevens, Luca Antiga, Thomas Viehmann| [[pdf]](https://pytorch.org/assets/deep-learning/Deep-Learning-with-PyTorch.pdf)|:heavy_check_mark:|

| Introdution to Probability| Jessica Hwang and Joseph K. Blitzstein | [[Google Drive]](https://drive.google.com/file/d/1VmkAAGOYCTORq1wxSQqy255qLJjTNvBI/view)|:x:|

|Ml Primer|Mihail Eric| [[pdf]](https://www.confetti.ai/assets/ml-primer/ml_primer.pdf) |:heavy_check_mark:|

|Mathematics For Machine Learning|Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong|[[github]](https://github.com/mml-book/mml-book.github.io) [[pdf]](https://mml-book.github.io/book/mml-book.pdf)|:heavy_check_mark:|

|Foundations of Data Science|Avrim Blum, John Hopcroft, Ravindran Kannan| [[pdf]](https://www.cs.cornell.edu/jeh/book.pdf)|:heavy_check_mark:|

|Think Stats|Allen Downey|[[github]](https://github.com/AllenDowney/ThinkStats2) [[pdf]](https://greenteapress.com/thinkstats/thinkstats.pdf)|:heavy_check_mark:|

|Math4ml|Garrett Thomas|[[github]](https://github.com/gwthomas/math4ml) [[pdf]](https://gwthomas.github.io/docs/math4ml.pdf)|:heavy_check_mark:|

|Think bayes|Allen Downey|[[github]](https://github.com/AllenDowney/ThinkBayes) [[html]](http://www.greenteapress.com/thinkbayes/html/index.html) [[pdf]](http://www.greenteapress.com/thinkbayes/thinkbayes.pdf)|:heavy_check_mark:|

|Think python 2|Allen Downey|[[pdf]](http://greenteapress.com/thinkpython2/thinkpython2.pdf)|:heavy_check_mark:|

|Intermediate python|Muhammad Yasoob Ullah Khalid|[[pdf]](https://buildmedia.readthedocs.org/media/pdf/intermediatepythongithubio/latest/intermediatepythongithubio.pdf)|:heavy_check_mark:|

|Pattern Recognition and Machine Learning|Christopher Bishop|[[pdf]](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf)|:heavy_check_mark:|  

|Computer Age Statistical Inference|Bradley Efron, Trevor Hastie|[[pdf]](https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf)|:heavy_check_mark:|

|An Introduction to Statistical Learning|Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani|[[pdf]](https://statlearning.com/ISLR%20Seventh%20Printing.pdf)|:heavy_check_mark:|

|The Elements ofStatistical Learning|Trevor Hastie, Robert Tibshirani, Jerome Friedman|[[pdf]](https://web.stanford.edu/~hastie/Papers/ESLII.pdf)|:heavy_check_mark:|