Machine Learning

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions.

Machine Learning Books

Hands-On Machine Learning with Scikit-Learn and TensorFlow

Pattern Recognition and Machine Learning (Information Science and Statistics)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Machine Learning: A Probabilistic Perspective

Machine Learning (McGraw-Hill International Editions Computer Science Series)

Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

Information Theory, Inference, and Learning Algorithms

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Artificial Intelligence: A Modern Approach

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Lists

Gödel, Escher, Bach by Douglas R. Hofstadter

The Human Use of Human Beings by Norbert Wiener

Algorithms to Live By by Brian Christian

Books on (machine) learning - how we and computers learn and 'think'

21 books — 5 voters

Reinforcement Learning by Richard S. Sutton

Information Theory, Inference, and Learning Algorithms by David J.C. MacKay

Pattern Recognition and Machine Learning by Christopher M. Bishop

Foundations of Machine Learning by Mehryar Mohri

Handbook of Practical Logic and Automated Reasoning by John E. Harrison

Machine Learning Year 3 (MCSL)

32 books — 9 voters

At the Interface of Algebra and Statistics by Tai-Danae Bradley

Mathematics for Human Flourishing by Francis Su

Quantum Computation and Quantum Information by Michael A. Nielsen

Categories for the Working Mathematician by Saunders Mac Lane

Category Theory in Context by Emily Riehl

At the Interface of Algebra and Statistics: Quantum Physics, Machine Learning, and Category Theory

23 books — 5 voters

An Introduction to Statistical Learning by Gareth James

Bayesian Data Analysis by Professor in the Department...

One Thousand Exercises in Probability by Geoffrey R. Grimmett

Nonlinear Dynamics and Chaos by Steven H. Strogatz

Statistical Science Year 2 (MCSL)

13 books — 9 voters

Linear Algebra Done Right by Sheldon Axler

Principles of Mathematical Analysis by Walter Rudin

Linear Algebra and Its Applications by Gilbert Strang

Real and Complex Analysis by Walter Rudin

Mathematics · Computer Science · Statistical Science · Machine Learning

143 books — 31 voters

Introduction to Quantum Mechanics by David J. Griffiths

The Elements of Statistical Learning by Trevor Hastie

Modern Quantum Mechanics by J.J. Sakurai

Options, Futures and Other Derivatives by John C. Hull

Classical Mechanics by Charles P. Poole Jr.

Mathematics Part II (University of Cambridge)

174 books — 12 voters

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Quotes Tagged “Machine Learning”

“ Mother-infant inter-brain synchrony algorithms of compassionate artificial intelligence and social robots are developed based on brain-to-brain synchrony of gaze, facial expressions and heart rhythms between mother and child. ”
― Amit Ray, Compassionate Artificial Intelligence

6 likes

“ While there's nothing new about financial panics, the role of AI/GPT is new and makes matters exponentially worse. That's not a criticism of AI which works as intended. It's a criticism of humans who don't understand the tool, over-rely on it, and allow it far too much autonomy in the trading process. ...more ”
― James Rickards, MoneyGPT: AI and the Threat to the Global Economy

1 likes

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