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Mathematics for Machine Learning
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4.33 avg rating — 247 ratings
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| 2 |
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Oeuvres Completes de Niels Henrik Abel: Nouvelle Edition: Nouvelle édition: Volume 1
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it was amazing 5.00 avg rating — 1 rating
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| 3 |
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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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| 4 |
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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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| 5 |
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Introduction to Machine Learning
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3.78 avg rating — 251 ratings
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| 6 |
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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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| 7 |
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Linear Algebra Done Right
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4.39 avg rating — 1,275 ratings
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| 8 |
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Predicting Structured Data
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3.57 avg rating — 7 ratings
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| 9 |
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Bayesian Reasoning and Machine Learning
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4.10 avg rating — 194 ratings
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| 10 |
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Information and Exponential Families in Statistical Theory
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liked it 3.00 avg rating — 2 ratings
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| 11 |
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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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| 12 |
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Geometry at Work (Mathematical Association of America Notes, Series Number 53)
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3.50 avg rating — 2 ratings
Emmy
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| 13 |
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Reproducing Kernel Hilbert Spaces in Probability and Statistics
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| 14 |
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Nonlinear Programming
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4.43 avg rating — 37 ratings
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| 15 |
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Convex Optimization Theory
by
4.33 avg rating — 12 ratings
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| 16 |
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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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| 17 |
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Probability and Measure (Wiley Series in Probability and Statistics Book 938)
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4.24 avg rating — 68 ratings
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| 18 |
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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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| 19 |
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Pattern Recognition and Machine Learning
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4.32 avg rating — 1,901 ratings
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| 20 |
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Numerical Optimization: Theoretical and Practical Aspects
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3.67 avg rating — 3 ratings
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| 21 |
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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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| 22 |
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On-Line Learning in Neural Networks (Publications of the Newton Institute, Series Number 17)
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| 23 |
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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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| 24 |
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Convex Optimization
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4.48 avg rating — 354 ratings
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| 25 |
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
by
4.20 avg rating — 49 ratings
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| 26 |
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Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by
3.85 avg rating — 13 ratings
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| 27 |
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Fundamentals of Statistical Exponential Families (Ims Lecture Notes-Monograph Ser.: Vol.9)
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4.50 avg rating — 2 ratings
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| 28 |
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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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| 29 |
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Statistical Inference
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4.17 avg rating — 396 ratings
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| 30 |
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Probability and Stochastics (Graduate Texts in Mathematics, Vol. 261)
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4.53 avg rating — 17 ratings
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| 31 |
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Deep Learning with R
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4.45 avg rating — 88 ratings
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| 32 |
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Deep Learning with Python
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4.57 avg rating — 1,397 ratings
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| 33 |
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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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| 34 |
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Numerical Linear Algebra and Applications
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4.19 avg rating — 21 ratings
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| 35 |
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Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 1)
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4.25 avg rating — 8 ratings
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| 36 |
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Non-Uniform Random Variate Generation
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4.50 avg rating — 2 ratings
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| 37 |
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Optimal Quadratic Programming Algorithms: With Applications to Variational Inequalities (Springer Optimization and Its Applications, 23)
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| 38 |
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Think Stats
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3.64 avg rating — 469 ratings
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| 39 |
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Real Analysis and Probability (Cambridge Studies in Advanced Mathematics, Series Number 74)
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3.61 avg rating — 18 ratings
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| 40 |
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Multivariate Statistics: A Vector Space Approach (Wiley Series in Probability and Statistics)
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4.50 avg rating — 2 ratings
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| 41 |
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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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4.43 avg rating — 129 ratings
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| 42 |
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KERNELS FOR STRUCTURED DATA
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3.33 avg rating — 3 ratings
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rated it 4 stars
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| 43 |
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Bayesian Data Analysis
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4.21 avg rating — 539 ratings
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| 44 |
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Random Number Generation and Monte Carlo Methods
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3.57 avg rating — 7 ratings
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| 45 |
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Markov Chain Monte Carlo in Practice
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3.70 avg rating — 23 ratings
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| 46 |
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Traces and Determinants of Linear Operators (Operator Theory: Advances and Applications, 116)
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| 47 |
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The Linear Algebra a Beginning Graduate Student Ought to Know
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really liked it 4.00 avg rating — 6 ratings
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| 48 |
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Matrix Computations (Johns Hopkins Studies in the Mathematical Sciences, 3)
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4.26 avg rating — 151 ratings
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| 49 |
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Deep Learning
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4.44 avg rating — 2,118 ratings
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| 50 |
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Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
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4.50 avg rating — 2 ratings
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| 51 |
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Probability: An Introduction
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4.10 avg rating — 39 ratings
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| 52 |
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Introduction to Probability
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4.26 avg rating — 23 ratings
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| 53 |
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An Introduction to Probability and Inductive Logic
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3.81 avg rating — 171 ratings
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