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Computers / Data Science / Machine Learning

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‹12›
Code to Joy

Code to Joy

Code to Joy

Why Everyone Should Learn a Little Programming

by Michael L. Littman

ISBN: 9780262546393

Publisher: The MIT Press

Pub Date: October 3, 2023

Forthcoming from the MIT Press
Probabilistic Machine Learning

Probabilistic Machine Learning

Probabilistic Machine Learning

Advanced Topics

by Kevin P. Murphy

ISBN: 9780262048439

Publisher: The MIT Press

Pub Date: August 15, 2023

An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in...
Causal Analysis

Causal Analysis

Causal Analysis

Impact Evaluation and Causal Machine Learning with Applications in R

by Martin Huber

ISBN: 9780262545914

Publisher: The MIT Press

Pub Date: August 1, 2023

Forthcoming from the MIT Press
Distributional Reinforcement Learning

Distributional Reinforcement Learning

Distributional Reinforcement Learning

by Marc G. Bellemare, Will Dabney and Mark Rowland

ISBN: 9780262048019

Publisher: The MIT Press

Pub Date: May 30, 2023

The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective.
The Little Learner

The Little Learner

The Little Learner

A Straight Line to Deep Learning

by Daniel P. Friedman and Anurag Mendhekar

Foreword by Guy L. Steele Jr. and Peter Norvig

ISBN: 9780262546379

Publisher: The MIT Press

Pub Date: February 21, 2023

A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.
Microprediction

Microprediction

Microprediction

Building an Open AI Network

by Peter Cotton

ISBN: 9780262047326

Publisher: The MIT Press

Pub Date: November 8, 2022

How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization.
Learning Kernel Classifiers

Learning Kernel Classifiers

Learning Kernel Classifiers

Theory and Algorithms

by Ralf Herbrich

ISBN: 9780262546591

Publisher: The MIT Press

Pub Date: November 1, 2022

An overview of the theory and application of kernel classification methods.
Introduction to Online Convex Optimization

Introduction to Online Convex Optimization, second edition

Introduction to Online Convex Optimization

by Elad Hazan

ISBN: 9780262046985

Publisher: The MIT Press

Pub Date: September 6, 2022

In many practical applications, the environment is so complex that it is not feasible to lay out a comprehensive theoretical model and use classical algorithmic theory and/or mathematical optimization....
Algorithms for Decision Making

Algorithms for Decision Making

Algorithms for Decision Making

by Mykel J. Kochenderfer, Tim A. Wheeler and Kyle H. Wray

ISBN: 9780262047012

Publisher: The MIT Press

Pub Date: August 16, 2022

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them.
High-Performance Big Data Computing

High-Performance Big Data Computing

High-Performance Big Data Computing

by Dhabaleswar K. Panda, Xiaoyi Lu and Dipti Shankar

ISBN: 9780262046855

Publisher: The MIT Press

Pub Date: August 2, 2022

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep learning.
‹12›

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