A list of freely available Machine Learning, Data Science and Statistics books.
| Book/Resource | Author(s) | Links | ⏬ |
|---|---|---|---|
| d2l-ai | Community | [github] [pdf] | ✔️ |
| Data Science Handbook | Jake Vanderplas | [github] [online] | ❌ |
| Deep Learning Book | Ian Goodfellow, Yoshua Bengio, Aaron Courville | [online] | ❌ |
| Deep Learning with Pytorch | Eli Stevens, Luca Antiga, Thomas Viehmann | [pdf] | ✔️ |
| Introdution to Probability | Jessica Hwang and Joseph K. Blitzstein | [Google Drive] | ❌ |
| Ml Primer | Mihail Eric | [pdf] | ✔️ |
| Mathematics For Machine Learning | Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong | [github] [pdf] | ✔️ |
| Foundations of Data Science | Avrim Blum, John Hopcroft, Ravindran Kannan | [pdf] | ✔️ |
| Think Stats | Allen Downey | [github] [pdf] | ✔️ |
| Math4ml | Garrett Thomas | [github] [pdf] | ✔️ |
| Think bayes | Allen Downey | [github] [html] [pdf] | ✔️ |
| Think python 2 | Allen Downey | [pdf] | ✔️ |
| Intermediate python | Muhammad Yasoob Ullah Khalid | [pdf] | ✔️ |
| Pattern Recognition and Machine Learning | Christopher Bishop | [pdf] | ✔️ |
| Computer Age Statistical Inference | Bradley Efron, Trevor Hastie | [pdf] | ✔️ |
| An Introduction to Statistical Learning | Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani | [pdf] | ✔️ |
| The Elements ofStatistical Learning | Trevor Hastie, Robert Tibshirani, Jerome Friedman | [pdf] | ✔️ |