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Adaptive Computation and Machine Learning series

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Probabilistic Machine Learning: Advanced Topics

Deep Learning

Foundations of Computer Vision

Reinforcement Learning, Second Edition: An Introduction

Gaussian Processes For Machine Learning

Introduction To Machine Learning, Fourth Edition

Machine Learning: A Probabilistic Perspective

Learning Theory from First Principles

Knowledge Graphs: Fundamentals, Techniques, And Applications

Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making

Machine Learning, Second Edition: A Probabilistic Perspective

Machine Learning for Data Streams: with Practical Examples in MOA

Probabilistic Graphical Models: Principles and Techniques

Learning Kernel Classifiers: Theory and Algorithms

Elements Of Causal Inference: Foundations And Learning Algorithms

Learning With Kernels: Support Vector Machines, Regularization, Optimization, And Beyond

Introduction To Natural Language Processing

Fairness and Machine Learning: Limitations and Opportunities

Foundations Of Machine Learning, Second Edition

Introduction To Statistical Relational Learning

Introduction To Online Convex Optimization, Second Edition

Machine Learning From Weak Supervision: An Empirical Risk Minimization Approach