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Reinforcement Learning : An Introduction

Deep Learning

Probabilistic Machine Learning : An Introduction

Probabilistic Machine Learning : Advanced Topics

Gaussian Processes for Machine Learning

Distributional Reinforcement Learning

Foundations of Machine Learning

Introduction to Online Convex Optimization, second edition

Introduction to Machine Learning

Elements of Causal Inference : Foundations and Learning Algorithms

Introduction to Natural Language Processing

Probabilistic Graphical Models : Principles and Techniques

Machine Learning from Weak Supervision : An Empirical Risk Minimization Approach

Knowledge Graphs : Fundamentals, Techniques, and Applications

Machine Learning in Non-Stationary Environments : Introduction to Covariate Shift Adaptation

Machine Learning for Data Streams : with Practical Examples in MOA

Introduction to Statistical Relational Learning

Boosting : Foundations and Algorithms

Introduction to Machine Learning

Introduction to Machine Learning

Foundations of Machine Learning

Bioinformatics : The Machine Learning Approach

Introduction to Machine Learning

Semi-Supervised Learning

Foundations of Computer Vision

Graphical Models for Machine Learning and Digital Communication

The Minimum Description Length Principle

Learning Kernel Classifiers : Theory and Algorithms

Reinforcement Learning : An Introduction

Causation, Prediction and Search

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