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

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

Information Theory, Inference, and Learning Algorithms

Artificial Intelligence: A Modern Approach

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Lists

The Elements of Statistical Learning by Trevor Hastie

The Visual Display of Quantitative Information by Edward R. Tufte

An Introduction to Statistical Learning by Gareth James

Data Science - Learning About Data

133 books — 121 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

The Age of AI and Our Human Future by Henry Kissinger

Machine Learning

102 books — 116 voters

The Hundred-Page Machine Learning Book by Andriy Burkov

Hands-On Machine Learning with Scikit-Learn, Keras, and Tenso... by Aurélien Géron

Mathematics for Machine Learning by Marc Peter Deisenroth

Machine Learning Year 1 (MCSL)

7 books — 11 voters

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

Foundations of Data Science by Avrim Blum

Stochastic Differential Equations by Bernt Øksendal

Algebraic Geometry and Statistical Learning Theory by Sumio Watanabe

Probability on Trees and Networks by Russell Lyons

Statistical Science Year 4 (MCSL)

20 books — 9 voters

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108 Books to Celebrate Hispanic Heritage Month

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Quotes Tagged “Machine Learning”

“ Emotions are essential parts of human intelligence. Without emotional intelligence, Artificial Intelligence will remain incomplete. ”
― Amit Ray, Compassionate Artificial Intelligence

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“ Confabulation, or hallucination, is ubiquitous in AI/GPT output already. Efforts to correct this by self-learning algos and back propagation are unlikely to solve the problem because they add to the complexity of the system as a whole, which increases the likelihood of emergent ghosts. The difficulty is that duplicity is hard to detect unless you're a subject matter expert in the topic or you conduct your own research to test its accuracy. This begs the question — if you have to be a subject mat ...more ”
― James Rickards, MoneyGPT: AI and the Threat to the Global Economy

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