TY  - GEN
AU  - Hardt, Moritz 
AU  - Recht, Benjamin
TI  - Patterns, predictions, and actions: foundations of machine learning
SN  - 9780691233734
U1  - 006.31 HAR  
PY  - 2022///
CY  - Princeton
PB  - Princeton University Press
KW  - Machine Learning
KW  - Optimization
KW  - Data Patterns
KW  - Linear Algebra
KW  - Calculus
KW  - Computer Science
N1  - Include Bibliography and Index
N2  - Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions.

Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions
Pays special attention to societal impacts and fairness in decision making
Traces the development of machine learning from its origins to today
Features a novel chapter on machine learning benchmarks and datasets
Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra
An essential textbook for students and a guide for researchers

https://press.princeton.edu/books/hardcover/9780691233734/patterns-predictions-and-actions
ER  -