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Mathematics for Machine Learning
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| 2 |
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All of Statistics: A Concise Course in Statistical Inference
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Probability and Statistics for Engineers and Scientists
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Bayesian Data Analysis
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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
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Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs, Series Number 5)
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Numerical Recipes: The Art of Scientific Computing
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4.32 avg rating — 157 ratings
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Think Stats
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Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
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Deep Learning with Python
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Machine Learning: A Probabilistic Perspective
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Statistical Inference
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Introduction to Machine Learning with Python: A guide for Data Scientists
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4.33 avg rating — 589 ratings
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Machine Learning (McGraw-Hill International Editions Computer Science Series)
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4.07 avg rating — 852 ratings
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Convex Optimization
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4.48 avg rating — 348 ratings
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Information Theory, Inference, and Learning Algorithms
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Pattern Recognition and Machine Learning
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BISHOP:NEURAL NETWORKS FOR PATTERN RECOGNITION PAPER (Advanced Texts in Econometrics (Paperback))
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Probabilistic Graphical Models: Principles and Techniques
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Probability Theory: The Logic of Science
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Numerical Linear Algebra
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4.28 avg rating — 151 ratings
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Bayesian Reasoning and Machine Learning
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Introduction to Linear Algebra (Gilbert Strang, 2)
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4.24 avg rating — 694 ratings
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Linear Algebra Done Right
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
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4.43 avg rating — 1,880 ratings
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All of Nonparametric Statistics
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4.13 avg rating — 39 ratings
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| 30 |
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An Introduction to Probability and Inductive Logic
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3.81 avg rating — 166 ratings
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| 31 |
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Introduction to Probability
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4.26 avg rating — 23 ratings
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| 32 |
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Probability: An Introduction
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4.10 avg rating — 39 ratings
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Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks, Series Number 3)
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4.35 avg rating — 17 ratings
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Morgan Kaufmann Series in Representation and Reasoning)
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Numerical Linear Algebra and Applications
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Deep Learning with R
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Probability and Stochastics (Graduate Texts in Mathematics, Vol. 261)
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Generalized Linear Models (Monographs on Statistics and Applied Probability)
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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Concentration Inequalities: A Nonasymptotic Theory of Independence
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Optimization by Vector Space Methods
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System Identification: Theory for the User
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Theory of Point Estimation
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Probability and Measure (Wiley Series in Probability and Statistics Book 938)
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Nonlinear Programming
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A History of Mathematics (3rd Edition)
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The Nature of Statistical Learning Theory
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STATISTICAL LEARNING THEORY
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Probability Essentials
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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
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Introduction to Numerical Analysis
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Independent Component Analysis
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Matrix Analysis
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Introduction to Machine Learning
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Understanding Machine Learning
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