Home Curriculum Learning Log Bookshelf
I'll keep a record of the books that I'm using and those which may become useful to me here.
| Title | Author | Free | Purchased |
|---|---|---|---|
| Machine Learning: A Probabilistic Perspective | Kevin Murphy | NO | YES |
| Pattern Recognition and Machine Learning | Christopher Bishop | NO | YES |
| Bayesian Reasoning and Machine Learning | David Barber | NO | YES |
| A First Look at Rigorous Probability Theory | Jeffrey Rosenthal | NO | YES |
| The Elements of Statistical Learning | Trevor Hastie | NO | YES |
| Python Machine Learning: 2nd Edition | Sebastian Raschka | NO | YES |
| All of Statistics: A Concise Course in Statistical Inference | Larry Wasserman | YES | YES |
| Advanced Data Analysis from an Elementary Point of View | Cosma Rohilla Shalizi | YES | NA |
| Think Stats: Probability and Statistics for Programmers | Allen B. Downey | YES | NA |
| Python for Data Analysis | Wes McKinney | NO | NO |
| The Theory of Probability: Explorations and Applications | Santosh S. Venkatesh | NO | NO |
| An Elementary Introduction to Statistical Learning Theory | Sanjeev Kulkarni | NO | NO |
| Fluent Python | Luciano Ramalho | NO | NO |