Notes on the Bibliography
Since I started building Algebrica in 2023, I have collected, read, and consulted hundreds of mathematics books, university lecture notes, papers, and many other resources, both in print and digital form. My goal has always been to build a knowledge base that brings together what I consider the best explanations available for each mathematical topic.
One aspect of mathematics I appreciate most is that there is always another perspective to discover. You may spend a long time studying a subject and then find another author who has a different explanation, another proof, a useful observation, or details that are missing elsewhere. Even when a topic seems complete, there is often something else worth reading.
Over time I have accumulated a large collection of material. A significant part of the work behind Algebrica has simply been reading, comparing sources, reconciling different approaches, and trying to include as many useful ideas as possible. My objective has always been to have explanations that are complete, rigorous, clear, and accessible.
Only a very small part of this work comes from my own background as a computer engineer. Most of it comes from the extraordinary amount of high-quality material that universities, authors, and publishers have made available over the years, both freely and commercially. Without those resources, Algebrica would not exist.
The bibliography below is my attempt to reconstruct the books, lecture notes, and other references that I have consulted while writing Algebrica. I hope it can also become a useful reference for anyone looking for reliable mathematical resources to study a topic in greater depth.
Algebra and number theory
- Abstract Algebra: Theory and Applications, Thomas W. Judson
- Algebra 2, Jay Abramson et al.
- Algebra: Abstract and Concrete, Frederick M. Goodman
- Algebra: Chapter 0, Paolo Aluffi
- Basic Algebra, Anthony W. Knapp
- Basic Category Theory, Tom Leinster
- Basic Mathematics, Serge Lang
- A Computational Introduction to Number Theory and Algebra, Victor Shoup
- A Course in Universal Algebra, Stanley N. Burris, H. P. Sankappanavar
- Elementary Number Theory: Primes, Congruences, and Secrets, William Stein
- Foundations of Module and Ring Theory, Robert Wisbauer
- The Great Story of Numbers, Egbert Rijke
- Group Theory, J. S. Milne
- Introduction to Modern Algebra, David Joyce
- Introduction to Modern Algebra, Darij Grinberg
- An Invitation to General Algebra and Universal Constructions, George M. Bergman
- Precalculus, Robert F. Blitzer
Linear algebra
- Advanced Linear Algebra, Steven Roman
- Discover Linear Algebra, Jeremy Sylvestre
- Fundamentals of Linear Algebra, James B. Carrell
- Fundamentals of Matrix Algebra, Gregory Hartman
- Introduction to Applied Linear Algebra, Stephen Boyd, Lieven Vandenberghe
- Introduction to Vectors and Tensors, Ray M. Bowen, C.-C. Wang
- Lectures on Applied Mathematics Part 1: Linear Algebra, Ray M. Bowen
- Linear Algebra, Jim Hefferon
- Linear Algebra, David Cherney, Tom Denton, Rohit Thomas, Andrew Waldron
- Linear Algebra as an Introduction to Abstract Mathematics, Isaiah Lankham, Bruno Nachtergaele, Anne Schilling
- Linear Algebra Done Right, Sheldon Axler
- Linear Algebra Done Wrong, Sergei Treil
- Linear Algebra for Computer Science, Manoj Thulasidas
- Linear Algebra with Applications, W. Keith Nicholson
- Matrix Calculus for Machine Learning and Beyond, Paige Bright, Alan Edelman, Steven G. Johnson
Geometry
- Analytic Geometry, Lewis Parker Siceloff, George Wentworth, David Eugene Smith
- Beginning in Algebraic Geometry, Emily Clader, Dustin Ross
- College Trigonometry, Carl Stitz, Jeff Zeager
- Differential Geometry: From Elastic Curves to Willmore Surfaces, Ulrich Pinkall, Oliver Gross
- Elementary College Geometry, Henry Africk
- Elementary Geometry from an Advanced Standpoint, Edwin E. Moise
- Plane Geometry, George Wentworth, David E. Smith
- The Rising Sea: Foundations of Algebraic Geometry, Ravi Vakil
- Trigonometry, Michael Corral
Topology
- Algebraic Topology, Allen Hatcher
- A Concise Course in Algebraic Topology, J. P. May
- Topology Without Tears, Sidney A. Morris
Calculus and real analysis
- Active Calculus: Single Variable, Matthew Boelkins, David Austin, Christina Safranski, Steven Schlicker
- Advanced Calculus, Lynn H. Loomis, Shlomo Sternberg
- Advanced Calculus, Gerald B. Folland
- Analysis of Functions of a Single Variable, Lawrence W. Baggett
- Basic Real Analysis, Anthony W. Knapp
- Calculus, Michael Spivak
- Calculus, Gilbert Strang
- Calculus in Context, James Callahan, David Cox, Kenneth Hoffman, Donal O'Shea, Harriet Pollatsek, Lester Senechal
- Calculus: Early Transcendentals, David Guichard
- Differential Calculus: From Practice to Theory, Eugene Boman, Robert Rogers
- Elementary Calculus: An Infinitesimal Approach, H. Jerome Keisler
- Honors Calculus, Pete L. Clark
- Integral Calculus: Mathematics 103, Leah Edelstein-Keshet
- Introduction to Analysis, John K. Hunter
- An Introduction to Measure Theory, Terence Tao
- Introduction to Real Analysis, Jiří Lebl
- Introduction to Real Analysis, William F. Trench
- Lecture Notes in Calculus I, Jakob Streipel
- Lecture Notes on Mathematical Analysis, Hsuan-Yi Liao
- Mathematical Analysis, Volume I, Elias Zakon
- Measure, Integration & Real Analysis, Sheldon Axler
- Methods of Real Analysis, Richard R. Goldberg
- Univariate Real Analysis, Martin Klazar
Complex analysis
- Complex Analysis, Russell W. Howell, John H. Mathews
- Complex Variables, Robert B. Ash, W. P. Novinger
- A First Course in Complex Analysis, Matthias Beck, Gerald Marchesi, Dennis Pixton, Lucas Sabalka
- Visual Complex Analysis, Tristan Needham
Ordinary differential equations
- Differential Equations I, Paul Selick
- Elementary Differential Equations, William F. Trench
- Notes on Diffy Qs, Jiří Lebl
Probability and statistics
- The Elements of Statistical Learning, Trevor Hastie, Robert Tibshirani, Jerome Friedman
- High-Dimensional Probability: An Introduction with Applications in Data Science, Roman Vershynin
- Introduction to Probability, Charles M. Grinstead, J. Laurie Snell
- Introduction to Probability, Joseph K. Blitzstein, Jessica Hwang
- Introduction to Probability, Dimitri P. Bertsekas, John N. Tsitsiklis
- An Introduction to Statistical Learning, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Lecture Notes on Probability, Statistics and Linear Algebra, C. H. Taubes
- OpenIntro Statistics, Christopher Barr, Mine Cetinkaya-Rundel, David Diez
- Probability and Statistics: The Science of Uncertainty, Michael J. Evans, Jeffrey S. Rosenthal
- Probability for Computer Scientists, Chris Piech
- Probability on Trees and Networks, Russell Lyons, Yuval Peres
Optimization
- Algorithms for Optimization, Mykel J. Kochenderfer, Tim A. Wheeler
- Branch-and-Price, Jacques Desrosiers, Marco Lübbecke, Guy Desaulniers, Jean Bertrand Gauthier
- Convex Optimization, Stephen Boyd, Lieven Vandenberghe
- Convex Optimization: Algorithms and Complexity, Sébastien Bubeck
- Convex Optimization: EE227BT Lecture Notes, Laurent El Ghaoui
- A First Course in Optimization, Charles L. Byrne
- Introduction to Online Convex Optimization, Elad Hazan
- Introduction to Optimization, Roland Herzog
- An Introduction to Optimization Algorithms, Thomas Weise
- Introduction to Stochastic Gradient Methods, Simon Weissmann
- Lecture Notes on Numerical Optimization, Miguel Á. Carreira-Perpiñán
- Lectures on Modern Convex Optimization, Aharon Ben-Tal, Arkadi Nemirovski
- A Modern Introduction to Online Learning, Francesco Orabona
- Optimization: Principles and Algorithms, Michel Bierlaire
Mathematical physics
- Classical Mechanics, Joel A. Shapiro
- Introduction to Advanced Engineering Mathematics and Analysis, Brian D. Wood
- Lectures on Classical Dynamics, David Tong
- Mathematical Methods for Physics, Niels Walet
- Mathematics for Physics, Michael Stone, Paul Goldbart
Foundations and general references
- Algebra, Topology, Differential Calculus, and Optimization Theory for Computer Science and Machine Learning, Jean Gallier, Jocelyn Quaintance
- The Architecture of Mathematics, Nicholas Bourbaki
- Book of Proof, Richard Hammack
- Everything You Always Wanted to Know About Mathematics (But Didn't Even Know to Ask), Brendan W. Sullivan
- Handbook of Mathematical Functions, Milton Abramowitz, Irene A. Stegun
- An Introduction to Formal Logic, Richard Zach
- Introduction to University Mathematics, James Munro
- Klotz Online Math Notes, Richard G. Klotz
- Maths 1, Andrew Rees
- The Princeton Companion to Mathematics, Timothy Gowers, June Barrow-Green, Imre Leader
- Proofs and Concepts, Dave Witte Morris, Joy Morris
- Pure Mathematics, Stuart Parsonson
Algorithms and computation
- Algorithms and Complexity, Herbert S. Wilf
- Applied Combinatorics, Mitchel T. Keller, William T. Trotter
- Discrete Structures, Andreas Klappenecker, Hyunyoung Lee
- Exploring Combinatorial Mathematics, Richard Grassl, Oscar Levin
- Foundations of Applied Mathematics, Jeffrey Humpherys, Tyler J. Jarvis
- Foundations of Computation, Carol Critchlow, David Eck
- Foundations of Data Science, Avrim Blum, John Hopcroft, Ravindran Kannan
- Graph Theory, Reinhard Diestel
- Graph Theory, Christopher Griffin
- Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
- Mathematical Methods for Computer Vision, Robotics, and Graphics, Justin Solomon
- Mathematics for Computer Science, Eric Lehman, F. Thomson Leighton, Albert R. Meyer
- Open Data Structures, Pat Morin
- Scientific Computing, Jeffrey R. Chasnov
- A Spiral Workbook for Discrete Mathematics, Harris Kwong
Machine learning and artificial intelligence
- Algorithms for Decision Making, Mykel J. Kochenderfer, Tim A. Wheeler, Kyle H. Wray
- Artificial Intelligence: A Modern Approach, Stuart Russell, Peter Norvig
- Computing Neural Network Gradients, Kevin Clark
- CS229 Lecture Notes on Machine Learning (Stanford), Andrew Ng, Tengyu Ma
- Dive into Deep Learning, Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
- Foundations of Large Language Models, Tong Xiao, Jingbo Zhu
- Foundations of Machine Learning, Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
- Information Theory, Inference, and Learning Algorithms, David J. C. MacKay
- An Introduction to Flow Matching and Diffusion Models, Peter Holderrieth, Ezra Erives
- The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer, Tianhua Chen
- Machine Learning Systems, Volume I: Foundations, Vijay Janapa Reddi
- Machine Learning Systems, Volume II: At Scale, Vijay Janapa Reddi
- Mathematical and Statistical Foundations of AI, Saman Siadati
- Mathematical Foundations of Deep Learning, Xiaojing Ye
- Mathematical Theory of Deep Learning, Philipp Petersen, Jakob Zech
- Mathematics for Machine Learning, Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
- Mathematics of Neural Networks, Bart M. N. Smets
- Pattern Recognition and Machine Learning, Christopher M. Bishop
- Patterns, Predictions, and Actions, Moritz Hardt, Benjamin Recht
- Transformers, Daniel Jurafsky, James H. Martin
- Understanding Deep Learning, Simon J. D. Prince
- Understanding Machine Learning: From Theory to Algorithms, Shai Shalev-Shwartz, Shai Ben-David