Books — Computer Systems & Machine Intelligence

Proofs & Discrete Mathematics

Book of ProofRichard Hammack
Discrete Mathematics and Its ApplicationsKenneth Rosen
Concrete MathematicsRonald Graham, Donald Knuth, Oren Patashnik

Linear Algebra

Introduction to Linear AlgebraGilbert Strang
Linear Algebra Done RightSheldon Axler
Numerical Linear AlgebraLloyd Trefethen, David Bau

Calculus

CalculusJames Stewart
CalculusMichael Spivak
Vector Calculus, Linear Algebra, and Differential FormsJohn Hubbard, Barbara Burke Hubbard

Probability

Introduction to ProbabilityJoseph Blitzstein, Jessica Hwang
A First Course in ProbabilitySheldon Ross
Introduction to ProbabilityDimitri Bertsekas, John Tsitsiklis

Statistics

All of StatisticsLarry Wasserman
An Introduction to Statistical LearningGareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Statistical InferenceGeorge Casella, Roger Berger

Optimization

First-Order Methods in OptimizationAmir Beck
Convex OptimizationStephen Boyd, Lieven Vandenberghe
Numerical OptimizationJorge Nocedal, Stephen Wright

Information Theory

Information Theory, Inference, and Learning AlgorithmsDavid MacKay
Elements of Information TheoryThomas Cover, Joy Thomas

Numerical Computing

Numerical Linear AlgebraLloyd Trefethen, David Bau
Scientific Computing: An Introductory SurveyMichael Heath
Accuracy and Stability of Numerical AlgorithmsNicholas Higham

Algorithms & Data Structures

Introduction to AlgorithmsThomas Cormen, Charles Leiserson, Ronald Rivest, Clifford Stein
Algorithm DesignJon Kleinberg, Éva Tardos
The Algorithm Design ManualSteven Skiena

Computability & Complexity

Introduction to the Theory of ComputationMichael Sipser
Computational Complexity: A Modern ApproachSanjeev Arora, Boaz Barak
Computational ComplexityChristos Papadimitriou

Computer Architecture

Computer Systems: A Programmer's PerspectiveRandal Bryant, David O'Hallaron
Computer Organization and DesignDavid Patterson, John Hennessy
Computer Architecture: A Quantitative ApproachJohn Hennessy, David Patterson

Operating Systems

Operating Systems: Three Easy PiecesRemzi Arpaci-Dusseau, Andrea Arpaci-Dusseau
Modern Operating SystemsAndrew Tanenbaum, Herbert Bos
The Design and Implementation of the FreeBSD Operating SystemMarshall Kirk McKusick, George Neville-Neil, Robert Watson

Concurrency & Parallelism

Is Parallel Programming Hard, And, If So, What Can You Do About It?Paul McKenney
The Art of Multiprocessor ProgrammingMaurice Herlihy, Nir Shavit
C++ Concurrency in ActionAnthony Williams

Networking

Computer Networking: A Top-Down ApproachJames Kurose, Keith Ross
Computer Networks: A Systems ApproachLarry Peterson, Bruce Davie
TCP/IP Illustrated, Volume 1W. Richard Stevens

Databases

Database InternalsAlex Petrov
Designing Data-Intensive ApplicationsMartin Kleppmann
Database Management SystemsRaghu Ramakrishnan, Johannes Gehrke

Distributed Systems

Designing Data-Intensive ApplicationsMartin Kleppmann
Distributed SystemsAndrew Tanenbaum, Maarten van Steen
Distributed AlgorithmsNancy Lynch

Compilers

Crafting InterpretersRobert Nystrom
Engineering a CompilerKeith Cooper, Linda Torczon
Compilers: Principles, Techniques, and ToolsAlfred Aho, Monica Lam, Ravi Sethi, Jeffrey Ullman

Performance Engineering

Performance Analysis and Tuning on Modern CPUsDenis Bakhvalov
Systems PerformanceBrendan Gregg
The Art of Computer Systems Performance AnalysisRaj Jain

Classical Machine Learning

Understanding Machine Learning: From Theory to AlgorithmsShai Shalev-Shwartz, Shai Ben-David
Probabilistic Machine Learning: An IntroductionKevin Murphy
The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani, Jerome Friedman

Neural Networks & Deep Learning

Understanding Deep LearningSimon Prince
Deep LearningIan Goodfellow, Yoshua Bengio, Aaron Courville
Dive into Deep LearningAston Zhang, Zachary Lipton, Mu Li, Alexander Smola

Computer Vision

Computer Vision: Algorithms and ApplicationsRichard Szeliski
Computer Vision: Models, Learning, and InferenceSimon Prince
Computer Vision: A Modern ApproachDavid Forsyth, Jean Ponce

Transformers & Language Models

Speech and Language ProcessingDan Jurafsky, James Martin
Build a Large Language Model (From Scratch)Sebastian Raschka
Introduction to Natural Language ProcessingJacob Eisenstein

Generative Modeling

Understanding Deep LearningSimon Prince
Probabilistic Machine Learning: Advanced TopicsKevin Murphy
Generative Deep LearningDavid Foster

Reinforcement Learning

Reinforcement Learning and Optimal ControlDimitri Bertsekas
Reinforcement Learning: An IntroductionRichard Sutton, Andrew Barto
Algorithms for Reinforcement LearningCsaba Szepesvári

GPU Computing

Efficient Processing of Deep Neural NetworksVivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer
Programming Massively Parallel ProcessorsDavid Kirk, Wen-mei Hwu
Professional CUDA C ProgrammingJohn Cheng, Max Grossman, Ty McKercher

ML Compilers

Efficient Processing of Deep Neural NetworksVivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer
Machine Learning Systems: Design and ImplementationLuo Mai, Hao Dong, Luo Cheng
Engineering a CompilerKeith Cooper, Linda Torczon

Distributed ML / Training Systems

Machine Learning Systems: Design and ImplementationLuo Mai, Hao Dong, Luo Cheng
Designing Data-Intensive ApplicationsMartin Kleppmann
Distributed AlgorithmsNancy Lynch

ML Systems

Efficient Processing of Deep Neural NetworksVivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer
Machine Learning Systems: Design and ImplementationLuo Mai, Hao Dong, Luo Cheng
Designing Machine Learning SystemsChip Huyen

Quantization / Efficient Models

Understanding Deep LearningSimon Prince
Efficient Processing of Deep Neural NetworksVivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer
Machine Learning Systems: Design and ImplementationLuo Mai, Hao Dong, Luo Cheng