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References from:
Deisenroth, Marc Peter, A. Aldo Faisal and Cheng Soon Ong. Mathematics for Machine Learning. Cambridge University Press, 2020.
The book is made freely available by the authors at:
https://mml-book.com
Deisenroth, Marc Peter, A. Aldo Faisal and Cheng Soon Ong. Mathematics for Machine Learning. Cambridge University Press, 2020.
The book is made freely available by the authors at:
https://mml-book.com
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| 1 |
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Mathematics for Machine Learning
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| 2 |
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
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| 3 |
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Deep Learning
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| 4 |
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Information Theory, Inference, and Learning Algorithms
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4.52 avg rating — 486 ratings
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| 5 |
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Pattern Recognition and Machine Learning
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| 6 |
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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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4.42 avg rating — 126 ratings
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| 7 |
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Deep Learning with Python
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| 8 |
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Convex Optimization
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4.48 avg rating — 345 ratings
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| 9 |
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Probability Theory: The Logic of Science
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4.40 avg rating — 650 ratings
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| 9 |
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Numerical Linear Algebra
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4.28 avg rating — 148 ratings
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| 11 |
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Linear Algebra Done Right
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| 12 |
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Introduction to Linear Algebra (Gilbert Strang, 2)
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| 13 |
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Introduction to Machine Learning with Python: A guide for Data Scientists
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| 13 |
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Machine Learning: A Probabilistic Perspective
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| 13 |
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Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
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| 16 |
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Matrix Computations (Johns Hopkins Studies in the Mathematical Sciences, 3)
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4.26 avg rating — 149 ratings
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| 16 |
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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
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4.25 avg rating — 757 ratings
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| 18 |
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Bayesian Data Analysis
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4.21 avg rating — 535 ratings
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| 18 |
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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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| 20 |
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All of Statistics: A Concise Course in Statistical Inference
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4.25 avg rating — 390 ratings
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| 21 |
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Nonlinear Programming
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4.43 avg rating — 37 ratings
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| 22 |
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Concentration Inequalities: A Nonasymptotic Theory of Independence
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4.56 avg rating — 18 ratings
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| 22 |
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Probability and Statistics for Engineers and Scientists
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4.08 avg rating — 413 ratings
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| 24 |
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Optimization by Vector Space Methods
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4.51 avg rating — 37 ratings
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| 25 |
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Deep Learning with R
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4.45 avg rating — 87 ratings
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| 26 |
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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
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4.49 avg rating — 71 ratings
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| 27 |
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Probability and Stochastics (Graduate Texts in Mathematics, Vol. 261)
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4.50 avg rating — 16 ratings
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| 28 |
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Independent Component Analysis
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4.47 avg rating — 15 ratings
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| 29 |
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Bayesian Reasoning and Machine Learning
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4.10 avg rating — 193 ratings
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| 30 |
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Probabilistic Graphical Models: Principles and Techniques
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4.19 avg rating — 257 ratings
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| 31 |
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Causality
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4.17 avg rating — 326 ratings
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| 32 |
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BISHOP:NEURAL NETWORKS FOR PATTERN RECOGNITION PAPER (Advanced Texts in Econometrics (Paperback))
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4.11 avg rating — 171 ratings
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| 33 |
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Statistical Inference
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4.16 avg rating — 390 ratings
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| 34 |
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Machine Learning (McGraw-Hill International Editions Computer Science Series)
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4.06 avg rating — 852 ratings
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| 35 |
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Fundamentals of Convex Analysis
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it was amazing 5.00 avg rating — 5 ratings
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| 36 |
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Support Vector Machines
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4.56 avg rating — 9 ratings
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| 37 |
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Theory of Probability
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4.89 avg rating — 9 ratings
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3 people voted
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| 38 |
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Convex Optimization Theory
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4.33 avg rating — 12 ratings
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| 38 |
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Think Stats
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3.64 avg rating — 466 ratings
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| 40 |
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Introduction to Machine Learning
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3.77 avg rating — 249 ratings
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| 41 |
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Convex Analysis and Nonlinear Optimization: Theory and Examples (CMS Books in Mathematics)
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4.33 avg rating — 9 ratings
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| 42 |
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Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics)
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4.20 avg rating — 10 ratings
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| 43 |
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Convex Analysis
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4.44 avg rating — 27 ratings
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| 44 |
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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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| 45 |
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A History of Mathematics (3rd Edition)
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4.32 avg rating — 56 ratings
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| 46 |
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Probability and Measure (Wiley Series in Probability and Statistics Book 938)
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4.21 avg rating — 66 ratings
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| 46 |
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Matrix Analysis
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4.36 avg rating — 61 ratings
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| 46 |
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Understanding Machine Learning
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4.20 avg rating — 131 ratings
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| 49 |
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Categorical Data Analysis (Wiley Series in Probability and Statistics)
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4.23 avg rating — 82 ratings
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| 50 |
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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4.19 avg rating — 47 ratings
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| 51 |
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Morgan Kaufmann Series in Representation and Reasoning)
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4.29 avg rating — 75 ratings
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| 52 |
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Numerical Linear Algebra and Applications
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4.20 avg rating — 20 ratings
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| 53 |
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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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| 54 |
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Introduction to Probability
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4.26 avg rating — 23 ratings
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| 55 |
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Handbook of the History of Logic, Volume 10: Inductive Logic
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Dov M. Gabbay (editor)
4.75 avg rating — 4 ratings
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2 people voted
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| 56 |
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Information Geometry and Its Applications (Applied Mathematical Sciences, 194)
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4.57 avg rating — 7 ratings
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| 57 |
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Probability via Expectation
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4.40 avg rating — 5 ratings
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| 58 |
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All of Nonparametric Statistics
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4.13 avg rating — 39 ratings
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| 59 |
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Probability Essentials
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| 59 |
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Introduction to Numerical Analysis
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4.13 avg rating — 15 ratings
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| 59 |
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The Nature of Statistical Learning Theory
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4.26 avg rating — 34 ratings
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| 59 |
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STATISTICAL LEARNING THEORY
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4.23 avg rating — 22 ratings
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| 63 |
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Theory of Point Estimation
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3.87 avg rating — 23 ratings
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| 64 |
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System Identification: Theory for the User
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4.18 avg rating — 22 ratings
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| 65 |
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Generalized Linear Models (Monographs on Statistics and Applied Probability)
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4.04 avg rating — 26 ratings
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| 66 |
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Gaussian Processes for Machine Learning
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4.17 avg rating — 108 ratings
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| 67 |
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Observation and Experiment: An Introduction to Causal Inference
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4.35 avg rating — 54 ratings
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| 68 |
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Linear Algebra
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3.92 avg rating — 114 ratings
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| 69 |
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Probability: An Introduction
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4.10 avg rating — 39 ratings
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| 70 |
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The Bootstrap and Edgeworth Expansion (Springer Series in Statistics)
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| 70 |
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A Primer to the 42 Most commonly used Machine Learning Algorithms (With Code Samples). (Artificial Intelligence Book 1)
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Murat Durmus (Goodreads Author)
4.20 avg rating — 10 ratings
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| 72 |
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Oeuvres Completes de Niels Henrik Abel: Nouvelle Edition: Nouvelle édition: Volume 1
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| 72 |
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A First Course in Dynamics: with a Panorama of Recent Developments
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| 74 |
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Kernel Methods for Pattern Analysis
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3.96 avg rating — 28 ratings
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| 75 |
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Theory of Linear Operators in Hilbert Space (Dover Books on Mathematics)
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4.20 avg rating — 10 ratings
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| 75 |
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Probability
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3.92 avg rating — 26 ratings
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| 77 |
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Handbook of Linear Algebra
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Leslie Hogben (Editor)
really liked it 4.00 avg rating — 5 ratings
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| 77 |
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Minimization Methods for Non-Differentiable Functions (Springer Series in Computational Mathematics)
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4.50 avg rating — 4 ratings
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| 79 |
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Predicting Structured Data
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Gökhan Bakir (Editor)
3.57 avg rating — 7 ratings
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| 80 |
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Information and Exponential Families in Statistical Theory
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| 81 |
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Latent Variable Models and Factor Analysis: A Unified Approach
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4.25 avg rating — 4 ratings
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| 82 |
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Geometry at Work (Mathematical Association of America Notes, Series Number 53)
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Catherine A. Gorini (Editor)
3.50 avg rating — 2 ratings
score: 89,
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| 82 |
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Advances in Kernel Methods: Support Vector Learning
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Bernhard Schölkopf (Editor)
3.67 avg rating — 3 ratings
score: 89,
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| 84 |
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Reproducing Kernel Hilbert Spaces in Probability and Statistics
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| 84 |
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Spline Models for Observational Data (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 59)
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3.67 avg rating — 3 ratings
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| 86 |
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Mathematical Statistics: Basic Ideas and Selected Topics, Vol I (2nd Edition)
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3.63 avg rating — 19 ratings
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| 86 |
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Testing Statistical Hypotheses
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3.65 avg rating — 17 ratings
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| 88 |
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Linear Algebra (Springer Undergraduate Mathematics Series)
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3.83 avg rating — 6 ratings
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| 89 |
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Numerical Optimization: Theoretical and Practical Aspects
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3.67 avg rating — 3 ratings
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| 90 |
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On-Line Learning in Neural Networks (Publications of the Newton Institute, Series Number 17)
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David Saad (Editor)
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| 90 |
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Matrix Differential Calculus with Applications in Statistics and Econometrics (Wiley Series in Probability and Statistics)
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3.90 avg rating — 10 ratings
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| 92 |
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Low Rank Approximation: Algorithms, Implementation, Applications
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| 93 |
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Stochastic Models, Estimation and Control: Volume 1
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| 94 |
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Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
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Steve Brooks (Editor)
3.85 avg rating — 13 ratings
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| 95 |
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Fundamentals of Statistical Exponential Families (Ims Lecture Notes-Monograph Ser.: Vol.9)
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| 95 |
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Svd and Signal Processing
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M. Moonen (Editor)
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| 97 |
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Learning in Graphical Models
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Michael I. Jordan (Editor)
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| 98 |
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An Introduction to Copulas (Springer Series in Statistics)
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3.60 avg rating — 10 ratings
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| 99 |
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Lectures on Convex Optimization (Springer Optimization and Its Applications, 137)
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4.43 avg rating — 7 ratings
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| 100 |
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The Relational Model for Database Management: Version 2
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3.92 avg rating — 13 ratings
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