Big Books of Spring
AI Doctor by Ronald M. RazmiPattern Recognition and Machine Learning by Christopher M. BishopUnmasking AI by Joy BuolamwiniThe Coming Wave by Mustafa SuleymanThe Elements of Statistical Learning by Trevor Hastie
Machine Learning
2nd out of 102 books — 111 voters
Windows 11 by Allan FaringtonIntroduction to Algorithms by Thomas H. CormenAn Introduction to Statistical Learning by Gareth JamesPattern Recognition and Machine Learning by Christopher M. BishopThe Algorithm Design Manual by Steven S. Skiena
Computer Science, Machine Learning and Data Science
4th out of 43 books — 82 voters

Calculus by Michael SpivakAlgebra by Paolo AluffiVisual Complex Analysis by Tristan NeedhamA Book of Abstract Algebra by Charles C. PinterPrinciples of Mathematical Analysis by Walter Rudin
Undergraduate Mathematics
75th out of 571 books — 37 voters
Abstract Algebra by David S. DummitLinear Algebra Done Right by Sheldon AxlerPrinciples of Mathematical Analysis by Walter RudinReal and Complex Analysis by Walter RudinThe Princeton Companion to Mathematics by Timothy Gowers
Mathematics · Computer Science · Statistical Science · Machine Learning
43rd out of 143 books — 30 voters

AI Doctor by Ronald M. RazmiDeep Utopia by Nick BostromCo-Intelligence by Ethan MollickSuperintelligence by Nick BostromUnmasking AI by Joy Buolamwini
Best machine learning books
17th out of 86 books — 78 voters
Differential Forms in Algebraic Topology by Raoul BottMathematical Methods of Classical Mechanics by Vladimir I. ArnoldIntroduction to Smooth Manifolds by John M. LeeCategories for the Working Mathematician by Saunders Mac LaneThe Arithmetic of Elliptic Curves by Joseph H. Silverman
Mathematics Part III (University of Cambridge)
11th out of 270 books — 13 voters

An Introduction to Manifolds by Loring W. TuDifferential Forms in Algebraic Topology by Raoul BottAlgebra by Serge LangSheaves in Geometry and Logic by Saunders MacLaneNumbers by Heinz-Dieter Ebbinghaus
Best of Springer Mathematics
62nd out of 500 books — 35 voters
Mathematics for Machine Learning by Marc Peter DeisenrothThe Elements of Statistical Learning by Trevor HastieDeep Learning by Ian GoodfellowInformation Theory, Inference, and Learning Algorithms by David J.C. MacKayPattern Recognition and Machine Learning by Christopher M. Bishop
Mathematics for Machine Learning
5th out of 120 books — 13 voters

Reinforcement Learning by Richard S. SuttonInformation Theory, Inference, and Learning Algorithms by David J.C. MacKayPattern Recognition and Machine Learning by Christopher M. BishopFoundations of Machine Learning by Mehryar MohriHandbook of Practical Logic and Automated Reasoning by John E. Harrison
Machine Learning Year 3 (MCSL)
3rd out of 32 books — 9 voters
Computational Complexity by Sanjeev AroraQuantum Computation and Quantum Information by Michael A. NielsenIntroduction to the Theory of Computation by Michael SipserThe Nature of Computation by Cristopher MooreIntroduction to Algorithms by Thomas H. Cormen
Theoretical Computer Science (MMath)
8th out of 57 books — 6 voters

Machine Learning with Neural Networks by Michael TaylorThe Math of Neural Networks by Michael TaylorMachine Learning by Samuel HackPattern Recognition and Machine Learning by Christopher M. BishopMachine Learning Mathematics by Samuel Hack
Building Artificial Neural Networks
4th out of 16 books — 13 voters
AI Doctor by Ronald M. RazmiLife 3.0 by Max TegmarkThe Book of Why by Judea PearlSuperintelligence by Nick BostromA Brief History of Intelligence by Max Solomon Bennett
Best Popular Computer Science Books on Goodreads
217th out of 293 books — 130 voters

Designing Data-Intensive Applications by Martin KleppmannMachine Learning Engineering by Andriy BurkovHands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien GéronAI Engineering by Chip HuyenMachine Learning Design Patterns by Valliappa Lakshmanan
ML/DL/AI Reading List
7th out of 28 books — 1 voter
Machine Learning by Samuel HackReal and Complex Analysis by Walter RudinVisual Complex Analysis by Tristan NeedhamOn Numbers and Games by John H. ConwayInside Interesting Integrals by Paul J. Nahin
Not Pop-Science - Mathematics
105th out of 111 books — 10 voters

Thinking, Fast and Slow by Daniel KahnemanThe Man Who Mistook His Wife for a Hat and Other Clinical Tales by Oliver SacksHow the Mind Works by Steven PinkerThe Blank Slate by Steven PinkerThe Selfish Gene by Richard Dawkins
Best Cognitive Science Books
403rd out of 414 books — 497 voters
Information Theory, Inference, and Learning Algorithms by David J.C. MacKayPattern Recognition and Machine Learning by Christopher M. BishopProbabilistic Reasoning in Intelligent Systems by Judea PearlProbability Theory by E.T. JaynesUnderstanding Machine Learning by Shai Shalev-Shwartz
kunstmatige intelligentie
2nd out of 8 books — 1 voter

The Structure of Scientific Revolutions by Thomas S. KuhnVision by David MarrIn the Land of Invented Languages by Arika OkrentThe Art of Memory by Frances A. YatesForaging Theory by David W. Stephens
Getting started in cognitive science (Gershman)
34th out of 36 books — 2 voters
Viral Justice by Ruha BenjaminGenius Makers by Cade MetzHuman Compatible by Stuart RussellThe Alignment Problem by Brian ChristianThe Singularity is Near by Ray Kurzweil
AI Book Recs: Add These to Your Reading List
13th out of 23 books — 1 voter

I, Robot by Isaac AsimovDo Androids Dream of Electric Sheep? by Philip K. Dick2001 by Arthur C. ClarkeNeuromancer by William GibsonThe Moon Is a Harsh Mistress by Robert A. Heinlein
Best Books on Artificial Intelligence
369th out of 433 books — 696 voters
All of Statistics by Larry WassermanConvex Optimization by Stephen BoydDeep Learning by Ian GoodfellowReinforcement Learning by Richard S. SuttonNumerical Algorithms by Justin Solomon
Computer-Math
6th out of 17 books — 3 voters

Computer Organization & Design by David A. PattersonEssential Software Development by AppJungle NET LLCThe C Programming Language by Brian W. KernighanHow to Design Programs by Matthias FelleisenThe C++ Programming Language by Bjarne Stroustrup
Computer Science on Books
37th out of 38 books — 2 voters
Linear Algebra and Learning from Data by Gilbert StrangIntroduction to Probability by Joseph K. BlitzsteinAll of Statistics by Larry WassermanStatistical Inference by George CasellaIntroduction to Linear Algebra by Gilbert Strang
A Mathematical Core for Data Scientists
7th out of 10 books — 2 voters

Theoretical Neuroscience by Peter DayanPattern Recognition and Machine Learning by Christopher M. BishopReinforcement Learning by Richard S. SuttonLehninger Principles of Biochemistry by David L. NelsonThe Feynman Lectures on Physics by Richard P. Feynman
Academic intersts
2nd out of 11 books — 1 voter
Doing Data Science by Cathy O'NeilAn Introduction to Statistical Learning by Gareth JamesAn Introduction to Probability Theory and Its Applications, V... by William FellerRegression and Other Stories by Andrew GelmanThe Book of Why by Judea Pearl
Only the best Probability, Applied Statistics and Data Science books
14th out of 36 books — 6 voters


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