Machine Learning: An Algorithmic Perspective, Second Edition (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Handbook of Floating-Point Arithmetic

Cognitive Robotics (Intelligent Robotics and Autonomous Agents series)

Computational Optimal Transport: With Applications to Data Science (Foundations and Trends(r) in Machine Learning)

Deep Learning with PyTorch Step-by-Step: A Beginner's Guide: Volume I: Fundamentals

The Machine Learning Solutions Architect Handbook: Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

Interactive Theorem Proving and Program Development: Coq’Art: The Calculus of Inductive Constructions (Texts in Theoretical Computer Science. An EATCS Series)

Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Hands-On Gradient Boosting with XGBoost and scikit-learn: Perform accessible machine learning and extreme gradient boosting with Python

Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection