Computers / Data Science / Machine Learning
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Understanding Deep Learning
ISBN: 9780262048644
Publisher: The MIT Press
Pub Date: December 5, 2023
An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.
Fairness and Machine Learning
Limitations and Opportunities
ISBN: 9780262048613
Publisher: The MIT Press
Pub Date: November 28, 2023
An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning.
Code to Joy
Why Everyone Should Learn a Little Programming
ISBN: 9780262546393
Publisher: The MIT Press
Pub Date: October 3, 2023
How we can get more joy from our machines by telling them what our hearts desire.
Probabilistic Machine Learning
Probabilistic Machine Learning
Advanced Topics
ISBN: 9780262048439
Publisher: The MIT Press
Pub Date: August 15, 2023
An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.
Causal Analysis
Impact Evaluation and Causal Machine Learning with Applications in R
ISBN: 9780262545914
Publisher: The MIT Press
Pub Date: August 1, 2023
A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.
Distributional Reinforcement Learning
Distributional Reinforcement Learning
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
A Straight Line to Deep Learning
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
Building an Open AI Network
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
Theory and Algorithms
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, second edition
Introduction to Online Convex Optimization
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....

Understanding Deep Learning
ISBN: 9780262048644
Publisher: The MIT Press
Pub Date: December 5, 2023
Fairness and Machine Learning
Limitations and Opportunities
ISBN: 9780262048613
Publisher: The MIT Press
Pub Date: November 28, 2023
Code to Joy
Why Everyone Should Learn a Little Programming
ISBN: 9780262546393
Publisher: The MIT Press
Pub Date: October 3, 2023
Probabilistic Machine Learning
Probabilistic Machine Learning
Advanced Topics
ISBN: 9780262048439
Publisher: The MIT Press
Pub Date: August 15, 2023
Causal Analysis
Impact Evaluation and Causal Machine Learning with Applications in R
ISBN: 9780262545914
Publisher: The MIT Press
Pub Date: August 1, 2023
Distributional Reinforcement Learning
Distributional Reinforcement Learning
ISBN: 9780262048019
Publisher: The MIT Press
Pub Date: May 30, 2023
The Little Learner
A Straight Line to Deep Learning
ISBN: 9780262546379
Publisher: The MIT Press
Pub Date: February 21, 2023
Microprediction
Building an Open AI Network
ISBN: 9780262047326
Publisher: The MIT Press
Pub Date: November 8, 2022
Learning Kernel Classifiers
Theory and Algorithms
ISBN: 9780262546591
Publisher: The MIT Press
Pub Date: November 1, 2022
Introduction to Online Convex Optimization, second edition
Introduction to Online Convex Optimization
ISBN: 9780262046985
Publisher: The MIT Press
Pub Date: September 6, 2022