#2 | | 4.33 |
#3 | How to Lie with Statistics | 3.85 |
#4 | Deep Learning - Ian Goodfellow
- Yoshua Bengio
- Aaron Courville
| 4.8 |
#5 | Neural Networks and Deep Learning | 5 |
#6 | Artificial intelligence - Stuart Russell
- Peter Norvig
| 3.75 |
#7 | | 2.95 |
#8 | Deep Learning with Python | 5 |
#9 | Programming Collective Intelligence: Building Smart Web 2.0 Applications | 2.75 |
#10 | Pattern Recognition and Machine Learning | 0 |
#11 | Introduction to Machine Learning with Python: A Guide for Data Scientists - Andreas C. Müller
- Sarah Guido
| 0 |
#12 | Data Science From Scratch: First Principles with Python | 4 |
#13 | Neural Network Methods for Natural Language Processing | 0 |
#14 | One Jump Ahead: Computer Perfection at Checkers | 0 |
#15 | An Introduction to Statistical Learning - Daniela Witten
- Trevor Hastie
- Robert Tibshirani
- Gareth James
| 0 |
#16 | The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind | 4 |
#17 | | 0 |
#18 | Paradigms of artificial intelligence programming | 0 |
#19 | Statistical Inference - George Casella
- Roger L. Berger
| 4 |
#20 | Superintelligence: Paths, Dangers, Strategies | 3.66 |
#21 | The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World | 3.19 |
#22 | | 0 |
#23 | The Elements of Statistical Learning: Data Mining, Inference, and Prediction - Trevor Hastie
- Robert Tibshirani
- Jerome Friedman
| 0 |
#24 | | 4 |
#25 | Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems | 5 |
#26 | | 3 |
#27 | | 5 |
#28 | | 0 |
#29 | Natural Language Processing Using Python | 0 |
#30 | Natural Language Processing in Action - Hobson Lane
- Cole Howard
- Hannes Hapke
| 5 |
#31 | Transformers for Natural Language Processing | 0 |
#32 | Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning | 0 |