| 1 |
|
Mathematics for Machine Learning
by
4.33 avg rating — 244 ratings
|
|
| 2 |
|
Deep Learning
by
4.44 avg rating — 2,113 ratings
|
|
| 3 |
|
Pattern Recognition and Machine Learning
by
4.32 avg rating — 1,897 ratings
|
|
| 4 |
|
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by
4.43 avg rating — 1,881 ratings
|
|
| 5 |
|
Introduction to Machine Learning
by
3.78 avg rating — 251 ratings
|
|
| 6 |
|
An Introduction to Probability and Inductive Logic
by
3.81 avg rating — 170 ratings
|
|
| 7 |
|
Matrix Computations (Johns Hopkins Studies in the Mathematical Sciences, 3)
by
4.26 avg rating — 150 ratings
|
|
| 8 |
|
Numerical Recipes: The Art of Scientific Computing
by
4.32 avg rating — 157 ratings
|
|
| 9 |
|
Bayesian Data Analysis
by
4.21 avg rating — 538 ratings
|
|
| 10 |
|
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs, Series Number 5)
by
4.43 avg rating — 129 ratings
|
|
| 11 |
|
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
by
4.24 avg rating — 755 ratings
|
|
| 12 |
|
Think Stats
by
3.64 avg rating — 467 ratings
|
|
| 13 |
|
Causality
by
4.17 avg rating — 329 ratings
|
|
| 14 |
|
Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
by
4.33 avg rating — 136 ratings
|
|
| 15 |
|
Deep Learning with Python
by
4.57 avg rating — 1,390 ratings
|
|
| 16 |
|
Introduction to Machine Learning with Python: A guide for Data Scientists
by
4.33 avg rating — 592 ratings
|
|
| 17 |
|
Statistical Inference
by
4.17 avg rating — 396 ratings
|
|
| 18 |
|
Machine Learning: A Probabilistic Perspective
by
4.34 avg rating — 520 ratings
|
|
| 19 |
|
Machine Learning (McGraw-Hill International Editions Computer Science Series)
by
4.07 avg rating — 855 ratings
|
|
| 20 |
|
Convex Optimization
by
4.48 avg rating — 349 ratings
|
|
| 21 |
|
Information Theory, Inference, and Learning Algorithms
by
4.52 avg rating — 488 ratings
|
|
| 22 |
|
BISHOP:NEURAL NETWORKS FOR PATTERN RECOGNITION PAPER (Advanced Texts in Econometrics (Paperback))
by
4.11 avg rating — 171 ratings
|
|
| 23 |
|
Probabilistic Graphical Models: Principles and Techniques
by
4.19 avg rating — 259 ratings
|
|
| 24 |
|
Introduction to Linear Algebra (Gilbert Strang, 2)
by
4.24 avg rating — 696 ratings
|
|
| 25 |
|
Bayesian Reasoning and Machine Learning
by
4.10 avg rating — 193 ratings
|
|
| 26 |
|
Linear Algebra Done Right
by
4.39 avg rating — 1,262 ratings
|
|
| 27 |
|
Numerical Linear Algebra
by
4.28 avg rating — 151 ratings
|
|
| 28 |
|
Probability Theory: The Logic of Science
by
4.41 avg rating — 656 ratings
|
|
| 29 |
|
All of Statistics: A Concise Course in Statistical Inference
by
4.26 avg rating — 400 ratings
|
|
| 30 |
|
Probability and Statistics for Engineers and Scientists
by
4.08 avg rating — 414 ratings
|
|