Mathematics

/sci/ Discord[]

To meet other scientifically/mathematically minded, join the official /sci/ discord server https://discord.gg/P8qfdSSrG3 (from the previous google-sites wiki).

Intro[]

Math at its core is about establishing truths separate from sensual qualities, seeking patterns based upon these truths, systematically removing contradictions/inconsistencies from the patterns, and formulating conjectures with all of the above in mind. It is the one true language apart from reality which makes it ironic that it is so useful.

Here we wish to provide resources which will help you to develop mathematical skills for where ever you choose to apply them.

Precalculus[]

Note that any autodidactic education requires a minimum amount of fundamentals, and to grasp the higher levels of math you absolutely need to understand the basic concepts known as precalculus, which is generally the math you will see up to high school. If you lack any of these fundamentals, you should refresh your knowledge at pages like Khan Academy or PatrickJMT. If you think you are fit, you can also directly start with calculus, although I would advise to skim a Precalculus book before you do so.

If you totally forgot everything or are a beginner, it is recommended you do the interactive exercises on Khan Academy because they are really helpful tools to quickly refresh your school knowledge up until calculus. You should do all the chapters up to Precalculus, that is: Early Math, Arithmetic, Pre-Algebra, Basic Geometry, Algebra I, Geometry, Algebra II, Trigonometry, Probability and Statistics. You don't need to listen to every video, but you should cover each exercise once to check if you understand it. Once you finish the Precalculus module, you can continue with your first book.

If you are still fit regarding math, you should at least do the precalculus module on Khan Academy to be sure you have grasped everything necessary. For a general overview on the topics to come, choose any book on precalculus, though I recommend one of the following:

Simmons' Precalculus Mathematics in a Nutshell: Geometry, Algebra, Trigonometry (Concise refresher)
Stewart's Precalculus: Mathematics for Calculus
Axler's Precalculus: A Prelude to Calculus
Cohen's Precalculus with Unit Circle Trigonometry
Stitz & Zeager's Precalculus (Free but might have a bit too much extra material)
Lang's Basic Mathematics

You can finish Stewart's book in a few months. It is already structured in a way that you can do 1-2 sections per day for 6 days and do a review day on the 7th. You will be familiar with most concepts in this book, but especially if you just come out of high school or have just finished Khan Academy from zero, it will be a good exercise for you.

Those of you who've never done precalculus, trigonometry, or even algebra 2 in high school or feel like you've forgotten all of it might be thinking that you should start with an algebra 2/3, college/intermediate algebra, or trigonometry book before starting a precalculus book since that's how it worked in high school, but don't be. If you take a look at Stewart's Algebra and Trigonometry book, all the content is mostly identical to his precalculus book. Similarly, Stewart's College Algebra and Trigonometry books also just recycle the corresponding material in his precalculus book.

If you're already at an advanced level and want to revisit basic mathematics just for fun, consider reading Linderholm's Mathematics Made Difficult: Handbook for the Perplexed.

Basic Euclidean geometry[]

Disclaimer: You don't really need to learn this stuff anymore unless you want to. Synthetic geometry (aka axiomatic or pure geometry) books use isn't how people usually go about solving geometry problems. They use analytic geometry (better named coordinate geometry) and solve problems by reducing them into algebra, trigonometry, and calculus problems. The axiomatic approach stuck around beyond the invention of coordinate geometry and calculus as a means to teach proofs and rigorous reasoning but that too has been replaced by Intro to Proofs (or Discrete Math) classes based on naive set theory and logic. With that said, classical Euclidean geometry becomes somewhat more interesting in the context of non-Euclidean or Klein geometries, which you can learn about later.

Kiselev's Geometry: Books I and II
1. Planimetry & Geometry
2. Stereometry (Euclid's Elements distilled)
Basic Geometry by Birkhoff and Beatley (Uses Birkhoff's axioms rather than the ones Euclid chose)
Geometry: A High School Course by Lang and Murrow
- A modern approach to rigorous geometry that covers somewhat different topics than other books do and isn't afraid to use coordinate

Some advanced 2nd course material:

Geometry Revisited by Coxeter and Greitzer
Advanced Euclidean Geometry by Posamentier
Advanced Euclidean Geometry (Dover Books) by Johnson
College Geometry: An Introduction to the Modern Geometry of the Triangle and the Circle (Dover Books) by Altshiller-Court

Elementary Algebra[]

Elements of Algebra by Euler (Don't let its age discourage you, it's one of the best books ever written on elementary algebra even 250~ years later. Minor errata: Euler makes a small mistake when defining division and multiplication by √-1. See this review. He writes that 1/√-1 = √(1/-1) = √-1 but this is incorrect as 1 = √-1/√-1 = √-1√-1 = (√-1)² = -1. Instead multiply by 1=√-1/√-1 to simplify it, 1/√-1 = 1/√-1 * √-1/√-1 = √-1/(√-1)² = -√-1. This may or may not be pointed out depending on your translation.)
Elementary Algebra for Schools by Knight and Hall ^{[Archive.org for the 1896 edition, Amazon for the 1906 edition]}

Some advanced "honors" books that cover extra material that hasn't been covered in algebra/public school courses for a century:

Algebra: An Elementary Text-Book - For the Higher classes of Secondary Schools and Colleges Volumes 1 & 2 by Chrystal
Higher Algebra: a Sequel to Elementary Algebra for Schools by Hall and Knight
College Algebra (AMS Chelsea Publishing) by Henry Burchard Fine

Vector Geometry[]

These books are the linear algebra approach to geometry. Many of the topics covered here are scattered throughout other courses so they're not required reading to progress. The material is collected & organized together here for beginners who want to see the modern approach geometric problems or for someone who wants to revise his geometric skills.

A Vector Space Approach to Geometry (Dover Books) by Melvin Hausner
Elementary Vector Geometry (Dover Books) by Seymour Schuster
Vector Geometry (Dover Books) by Gilbert de B. Robinson

Problem books[]

These elementary problem books are meant for additional non-routine practice, challenges & puzzles, killing time, preparing for school competitions and exams, or to steal interesting questions from when you're teaching or tutoring students.

Challenging Problems in Algebra (Dover Books) by Posamentier
Challenging Problems in Geometry (Dover Books) by Posamentier
The USSR Olympiad Problem Book: Selected Problems and Theorems of Elementary Mathematics (Dover Books) by Shklarsky, Chentzov, and Yaglom
103 Trigonometry Problems: From the Training of the USA IMO Team by Andreescu and Feng
104 Number Theory Problems: From the Training of the USA IMO Team by Andreescu
105 Algebra Problems from the AwesomeMath Summer Program by Andreescu
106 Geometry Problems from the AwesomeMath Summer Program by Andreescu
107 Geometry Problems from the Awesomemath Year-Round Program by Andreescu
108 Algebra Problems from the Awesomemath Year-Round Program by Andreescu
Problems From the Book and Straight From the Book by Andreescu
The Stanford Mathematics Problem Book (Dover Books) by Polya and Kilpatrick
Sequences, Combinations, Limits (Dover Books) by Gelfand, Gerver, Kirillov, Konstantinov, and Kushnirenko
Challenging Mathematical Problems With Elementary Solutions (Dover Books) by A.M. Yaglom and I.M. Yaglom
Hungarian Problem Book I-IV containing the Eötvös Mathematical Competitions from 1894–1963

The following have more advanced problems at the university level up to preparing for qualifying exams during graduate school

The Green Book of Mathematical Problems (Dover Books) by Hardy and Williams
The Red Book of Mathematical Problems (Dover Books) by Williams and Hardy
William Lowell Putnam Mathematical Competition: Problems & Solutions: 1938-1964
The William Lowell Putnam Mathematical Competition: Problems and Solutions 1965–1984
The William Lowell Putnam Mathematical Competition 1985-2000: Problems, Solutions and Commentary
Contests in Higher Mathematics: Miklos Schweitzer Competitions, 1962-1991 by Szekely
Problems in Mathematical Analysis I: Real Numbers, Sequences and Series by Kaczor and Nowak
Problems in Mathematical Analysis II: Continuity and Differentiation by Kaczor and Nowak
Problems in Mathematical Analysis III Integration by Kaczor and Nowak
A Collection of Problems on Complex Analysis (Dover Books) by Volkovyskii, Lunts, and Aramanovich
Problems in Group Theory (Dover Books) by Dixon
Problems and Theorems in Analysis I: Series, Integral Calculus, Theory of Functions by George Polya and Gabor Szegö
Problems and Theorems in Analysis II: Theory of Functions, Zeros, Polynomials, Determinants, Number Theory, Geometry by George Polya and Gabor Szegö
A Hilbert Space Problem Book by Halmos
Berkeley Problems in Mathematics by Paulo Ney de Souza and Jorge-Nuno Silva
Problems and Solutions in Mathematics (Major American Universities PH.D. Qualifying Questions and Solutions)
Puzzles in geometry that I know and love by Petrunin

Problem Solving and Heuristics[]

Some strategies on how to approach difficult problems to solve them exactly or heuristically and dealing with Fermi problems:

How to Solve It: A New Aspect of Mathematical Method by Polya
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin by Weinstein and Adam
Guesstimation 2.0: Solving Today's Problems on the Back of a Napkin by Weinstein and Edwards
Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving by Mahajan
The Art of Insight in Science and Engineering: Mastering Complexity by Mahajan
How to Solve It: Modern Heuristics by Michalewicz and Fogel
- Heuristics focusing on CS/optimization problems
Problem-Solving Through Problems by Larson
Solving Mathematical Problems: A Personal Perspective by Terence Tao
Putnam and Beyond by Gelca and Andreescu

Overview of Mathematics[]

What Is Mathematics? An Elementary Approach to Ideas and Methods by Richard Courant and Herbert Robbins
Prelude to Mathematics (Dover Books) by Sawyer
Concepts of Modern Mathematics (Dover Books) by Ian Stewart
Mathematics: Its Content, Methods and Meaning (Dover Books) by Aleksandrov, Kolmogorov, Lavrentev, Sobolev, Gel'fand, et al.
A Mathematical Gift: The Interplay Between Topology, Functions, Geometry, and Algebra I, II, III by Ueno et al.

Calculus[]

Calculus is the study of change (derivatives) and accumulation (integrals) of functions. These topics are linked by the Fundamental Theorem of Calculus which states informally that "the accumulation of the changes of a function" and "the change of the accumulation of a function" result in the original function. The rest of calculus is just spamming these ideas on various applications and situations.

Some students struggle with calculus but honestly it is a really straight forward subject, especially compared to other advanced subjects in math. As long as you pay attention and go in trying to learn, you should quickly end up joining the rest of the math students in calling it 'trivial' in retrospect. Don't set yourself up to failure by thinking you're not capable of learning it because it will all click once you look at it right.

Single Variable Calculus[]

The standards texts (Stewart, Rogawski, et al.) you see required for college classes are, in all honesty, quite terrible since they are not written with self-study in mind but just as a collection of exercises and a review of the basic methods. Do use them to practice calculus but not as a means to learn it.

For a well done intuitive approach using infinitesimals, which is the way everyone ends up thinking about calculus which is also technically nonstandard but by no means mathematically incorrect, Elementary Calculus: An Infinitesimal Approach by Jerome Keisler is a fantastic and free public domain book (also available in an inexpensive Dover paperback edition). If the infinitesimal approach intrigues you but you've already done a course in calculus or currently reading through another 1000 page book on calculus, Infinitesimal Calculus (Dover Books) by Henle and Kleinberg is a nice short 144 page book that develops the theory of infinitesimals in calculus in an accessible and clear manner. As you can probably infer from the page count, Henle's book doesn't have any material on the applications of calculus so don't use it as a standalone book to learn all of calculus from but as a supplement to see a different approach in understanding the subject the way it was originally invented.

For a rigorous standard (δ-ε) approach to the subject, your options are Calculus by Spivak or the classic Calculus, Vol. 1: One-Variable Calculus, with an Introduction to Linear Algebra by Apostol. Spivak's writing certainly has its fans but it sadly lacks much of the applications and motivation (related rates, optimization) that are standard in calculus making it hard to use on its own. Apostol's Calculus doesn't have this oversight and it's probably the best one to learn the material from on your own. Another rigorous option that also has copious amounts of physics applications, motivation, and intuition presented at the same time is Introduction to Calculus and Analysis, Volume I by Richard Courant and Fritz John. The book is a modern rewrite of the classic Differential and Integral Calculus by Richard Courant and includes the most material of the three and its exercise are the most difficult (perhaps a bit too difficult in places).

Other calculus books leave out the involved proofs, which you'll see later in analysis, and focus on conceptual understanding and applying calculus to accommodate weaker students or students that are less prepared in rigorous/abstract mathematics. This isn't a completely bad way of learning calculus but you might be annoyed by the occasional lack of explanation/justification in some isolated places. Some good books in this category are Calculus: An Intuitive and Physical Approach (Dover Books) by Kline, Calculus With Analytic Geometry by Simmons (contains a lot on history of the subject and its applications in physics and science), and A First Course in Calculus by Lang.

To just learn the methods of calculus, there are plenty of lectures on calculus for you to choose from on YouTube, such as 3Blue1Brown's intuitive Essence of Calculus series, and the videos of Martin Van Biezen, Sal Khan, PatrickJMT, and blackpenredpen

Multivariable and Vector Calculus[]

Again, the usual suspects you'll find assigned in college courses tend to make good exercise books but terrible introductions to the subject. Your options are the latter part of Keisler's book above for an infinitesimals approach; Lang's Calculus of Several Variables or the latter part of Simmons' book to continue with their approach for weaker and less prepared students; and Calculus, Vol. 2: Multi-Variable Calculus and Linear Algebra with Applications to Differential Equations and Probability by Apostol, or Introduction to Calculus and Analysis, Vol. II by Richard Courant and Fritz John (the paperback is split into 2 parts) to continue on with the standard rigorous approach. For another text that covers this material in a more geometric way, consider Callahan's Advanced Calculus: A Geometric View^[website].

The following texts take a slightly more abstract approach than Apostol or Courant and go a bit deeper into the subject by covering differential forms and manifolds. Most single semester courses on vector calculus do not have time to reasonably cover this material, and consequently is usually skipped until later, but this advanced perspective can greatly aid one's understanding of the subject. You could study this material either when you first learn multivariable calculus or when you want a second pass on the subject, after just learning the basic methods, to improve your understanding while deepening your knowledge by generalizing what you've seen before. They can also be used as supplements or stepping stone to an advanced multivariable analysis course.

C. H. Edwards Jr.'s Advanced Calculus of Several Variables (Dover Books)
Hubbard and Hubbard's Vector Calculus, Linear Algebra and Differential Forms: A Unified Approach
Shifrin's Multivariable Mathematics: Linear Algebra, Multivariable Calculus, and Manifolds (a bit expensive if you decide to purchase the book)
Harold M. Edwards' Advanced Calculus: A Differential Forms Approach
Bressoud's Second Year Calculus: From Celestial Mechanics To Special Relativity

Curves and Surfaces in ℝ² and ℝ³[]

This subject is the study of Geometry using the tools that you learned in Vector Calculus and serves as a preparation to more abstract approaches to Differential Geometry you'll see in the future. Most schools only quickly pass through the subject during multivariable calculus but it will help in the long run if you study the material early on.

Tapp's Differential Geometry of Curves and Surfaces
Pressley's Elementary Differential Geometry
Christian Bär's Elementary Differential Geometry
do Carmo's Differential Geometry of Curves and Surfaces (Dover Books) (standard book)

Ordinary Differential Equations[]

The standard text used in college courses is Elementary Differential Equations by Boyce and DiPrima, which many people do seem to like (not me however). A cheap and very good alternative is Ordinary Differential Equations by Tenenbaum & Pollard (Dover Books) which is perfect for self study. Other well written books are Differential Equations with Applications and Historical Notes by Simmons and Differential Equations by Ross.

Coddington's An Introduction to Ordinary Differential Equations (Dover Books)
Hirsch and Smale's Differential Equations, Dynamical Systems, and Linear Algebra
- A unified approach that combines linear algebra and ODE. The newer editions, featuring the author Devaney, does offer more applications plus an intro to chaos theory, but the older editions without Devaney is more rigorous. In either case, PDFs of both can be found rather easily.
Arnold's Ordinary Differential Equations (advanced)
- Requires some analysis
- Has a lot of intuition on smooth manifolds

Linear Algebra[]

When speaking of linear algebra, people refer to one of 2 complementary but different subjects: matrix algebra/computational linear algebra and theoretical linear algebra/finite vector space theory. Oddly enough, you could study them in any order but canonically you're typically expected to learn some matrix algebra first and then transition to vector spaces and/or more applied/numerical topics second. The necessary prerequisite knowledge is just precalculus but some calculus knowledge is useful and may appear in a few examples.

Matrix Algebra[]

For a first exposure to the subject there really isn't that much to learn. You typically cover systems of equations, matrix operations, Gaussian elimination (also known as row reduction), LU decomposition, determinants, eigenvectors and eigenvalues, and diagonalization possibly with a few additional fluff subjects to round out a whole course. Many times you can pick up this material while studying calculus or ODEs (like with Apostol or Hubbard²'s book) so you can just skip to more advanced material. Also, the introductory material in first few chapters of advanced textbooks are often good enough to learn matrix algebra from if you're in a rush.

But while some students seem to inhale these topics and quickly move on, others will need to take their time before operating with matrices becomes natural to them. A gentle introduction for learners with weaker math skills can be found in Matrices and Linear Algebra by Schneider and Barker. Learners with slightly better math abilities can benefit more from Matrices and Linear Transformations by Cullen which is aimed at STEM students and contains extra material at the end on advanced material. A free book for students seeking a honors introduction to linear algebra (and basic proofs) is Linear Algebra Done Wrong by Treil (Don't worry, the title is a pun on Axler's "done right" book below). Another popular free book is Hefferon's Linear Algebra. There's also a whole host of vulgarly over expensive textbooks used by college courses at this level (like Strang's Introduction to Linear Algebra, Lay's Linear Algebra and Its Applications, Friedberg's Elementary Linear Algebra, etc) but most of them aren't very good and even if they were, the first two aforementioned books above are far cheaper thanks to them being published by Dover and the last two are free. If you prefer learning from videos, you can get a very solid intro using the linear algebra playlists on Khan Academy, PatrickJMT, or Engineer4Free. Bonus is they are all free.

Applied Linear Algebra[]

For a first book in applied linear algebra, Linear Algebra and Its Applications by Strang is the standard text used but it is one of those love-it-or-hate-it texts. If you fall into the hate-it camp, then Meyer's Matrix Analysis and Applied Linear Algebra is a good alternative. After reading one of them, you'll be more than ready to move onto advanced numerical linear algebra and matrix analysis textbooks.

Finite-Dimensional Vector Spaces[]

To get started on the theoretical side of linear algebra you obviously should be familiar with the basics of proofs. Once you are, theory side has a lot of classic and well loved textbook to choose from:

Linear Algebra by Shilov (Dover Books)
Finite-Dimensional Vector Spaces by Halmos (Dover Books)
Linear Algebra by Friedberg, Insel, and Spence
Linear Algebra by Hoffman and Kunze

Of course there's also Linear Algebra done Right by Axler and on the one hand, the stuff he does is great... but on the other hand, he fucking HATES determinants and goes crazy avoiding them. Because of that you shouldn't use his book alone to learn from and you really should read Shilov alongside of it. But Axler certainly gives a unique development to the subject.

Refreshers and Advanced Books in LA[]

Now if you want a challenge, start off with Linear Algebra and Its Applications by Lax. It is good for learning linear algebra for the first time if you're a hot shot freshman and already know the basics of calculus and analysis, using it as a second book on linear algebra, or as a 3rd refresher book for those who are entering graduate school. Another good 3rd book for deeper linear algebra study, and if you have the abstract algebra background for it, is Roman's Advanced Linear Algebra. Abstract Linear Algebra by Curtis is a concise 162 page book that builds up the core of linear algebra from the beginning in a general abstract way and ends with Hurwitz's Theorem as a finale.

Linear Algebra and Geometry by Kostrikin & Manin is an excellent advanced book bridging Linear Algebra to many advanced topics including Lie algebras, category theory, Clifford algebras, affine and projective geometry, tensors and multilinear algebra, and many applications in quantum mechanics and physics.

Advanced Calculus[]

The term Advanced Calculus has come to mean different things over the course of the past century. During the first half of the 20th century, Advanced Calculus courses consisted of what's now commonly found in Multivariable and Vector Calculus possibly with some Differential Equations topics thrown in. Lately, it has been fashionable to call very watered down "Real Analysis" courses Advanced Calculus even though it's not advanced nor calculus and goes no deeper into analysis than a good rigorous calculus book does. Here Advanced Calculus means what the name implies, advanced topics in calculus (and tools from analysis) typically not found in the usual calculus sequence but still very useful for solving difficult problems in science, engineering, and mathematics.

Complex Variables[]

Complex variables (also known as complex calculus or applied complex analysis) is the generalization of calculus over the complex field and shares many parallels with multivariable/vector calculus.

A First Course in Complex Analysis with Applications by Zill and Shanahan
Fundamentals of Complex Analysis: With Applications to Engineering and Science by Saff and Snider
Complex Variables: Introduction and Applications by Ablowitz and Fokas ^[Errata]
Functions of a Complex Variable: Theory and Technique by Carrier, Krook, and Pearson

A good supplement to any of the above is Visual Complex Analysis by Needham. Once you've finished a book on complex variables, Conformal Mapping: Methods and Applications (Dover Books) by Schinzinger and Laura makes a nice supplement with many applications of conformal mapping in MechE/AeroE and EE.

Special Functions[]

Special functions used to be the subject of a second semester complex variables course until it was sucked into mathematical physics, advanced engineering mathematics and other similar courses. The problem with such courses is that they spend far too little time developing subject as they try to cover complex variables, PDEs, differential geometry, topology, variations, algebra, and numerical methods among other subjects at the same time. The following books give a more focused and fuller development of special functions:

Special Functions & Their Applications (Dover Books) by Lebedev
Special Functions for Scientists and Engineers (Dover Books) by Bell
The Functions of Mathematical Physics (Dover Books) by Hochstadt

For books with more mathematical theory:

Special Functions by Andrews, Askey, and Roy
A Course of Modern Analysis by Whittaker and Watson
Special Functions by X. Z. Wang and Guo (Great complement to Whittaker and Watson)

Whittaker and Watson has been the bible for special functions for over a century now. Part 1 contains a review of the essential real and complex analysis needed for Part 2 which details the major special functions.

Fourier Transforms[]

The Fourier transform and related transforms are powerful techniques used throughout STEM that convert a function into its frequency components. Tragically, many science and engineering programs can't find room for such a course in their curricula and try to get away with throwing in brief discussion of how to use them into the courses that require them. This in the end fails to create any conceptual understanding of what's going on beyond the mindless crank turning. These books will help you see the Fourier transform beyond just a 'trick' and be better equipped to apply them:

The Fourier Transform & Its Applications by Bracewell (Great for conceptual understanding)
Fourier Transforms: An Introduction for Engineers by Gray and Goodman
Linear Systems, Fourier Transforms, and Optics by Gaskill
A First Course in Fourier Analysis by Kammler

The subject matter overlaps considerably with EEE's Systems and Signals books. For more mathematical detailed books see the fourier analysis books below.

Calculus of Variations[]

Calculus of variations is the subject of finding functions that maximize or minimize some equation. For example, finding a path that minimizes the distance traveled from point a to b.

Calculus of Variations (Dover Books) by Gelfand and Fomin
Calculus of Variations: with Applications to Physics and Engineering (Dover Books) by Weinstock
Calculus of Variations (Dover Books) by Elsgolc

Integral Equations[]

Introduction to Integral Equations with Applications by Jerri
The Classical Theory of Integral Equations: A Concise Treatment by Zemyan
Integral Equations (Dover Books) by Tricomi
Linear Integral Equations by Kress
Singular Integral Equations: Boundary Problems of Function Theory and Their Application to Mathematical Physics (Dover Books) by Muskhelishvili (more advanced)

Asymptotics[]

Asymptotic Methods in Analysis (Dover Books on Mathematics) by de Bruijn
Asymptotic Expansions (Dover Books on Mathematics) by Erdelyi
Asymptotic Expansions of Integrals (Dover Books on Mathematics) by Bleistein and Handelsman
Asymptotics and Special Functions by Olver

Perturbation Theory[]

A First Look at Perturbation Theory (Dover Books on Physics) by Simmonds and Mann Jr (Primmer)
Introduction to Perturbation Methods by Holmes
Advanced Mathematical Methods for Scientists and Engineers: Asymptotic Methods and Perturbation Theory by Bender and Orszag
Perturbations: Theory and Methods by Murdock
Perturbation Theory for Linear Operators by Tosio Kato

Nonlinear Dynamics and Chaos[]

Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering by Strogatz ^{[Author's online course]}
Dynamical Systems (Dover Books on Mathematics) by Shlomo Sternberg ^[Free]
Introduction to Applied Nonlinear Dynamical Systems and Chaos by Wiggins

Obscure Topics[]

Integration Techniques[]

If you have read about Feynman, you may have heard his story of coming across Advanced Calculus by Woods and discovering the differentiating parameters under the integral sign^[1]^[2][3] trick and using it to his advantage over and over again. These books are in a similar vein, they contain many integration techniques like ∫f^-1(x) dx = xf^-1(x) - F(f^-1(x)) that aren't covered in a standard single variable calculus course but are accessible to anyone who's completed the course.

Irresistible Integrals: Symbolics, Analysis and Experiments in the Evaluation of Integrals by Boros and Moll
Inside Interesting Integrals: (with an introduction to contour integration) A Collection of Sneaky Tricks, Sly Substitutions, and Numerous Other Stupendously Clever, Awesomely Wicked, and Devilishly Seductive Maneuvers for Computing Nearly 200 Perplexing Definite Integrals From Physics, Engineering, and Mathematics (Plus 60 Challenge Problems with Complete, Detailed Solutions) by Nahin
(Almost) Impossible Integrals, Sums, and Series by Valean

Fractional Calculus[]

Just as you can iterate to get second derivatives and triple integrals, it's possible to extend the order of these operators from integers to fractions or to any real or complex number. For example, you can define a half derivative operator where if you apply it twice to a function, you get the usual derivative of that function. This is the domain of fractional calculus which has a wide variety of applications in many branches of physics and engineering. The idea of fractional calculus is an old one dating back to Leibniz in 1695 and its applications were examined by the electrical engineer Oliver Heaviside in the 1890s but the first textbook on the subject was only published in 1974 by Oldham and Spanier. Since then fractional calculus has steadily been gaining more attention but it still remains relatively unknown to many in the STEM field.

The Fractional Calculus: Theory and Applications of Differentiation and Integration to Arbitrary Order (Dover Books) by Oldham and Spanier
An Introduction to the Fractional Calculus and Fractional Differential Equations by Miller and Ross

Partial Differential Equations[]

Historically, the study of PDEs was a major impetus for the development of many results of analysis. Without this advanced math knowledge, the study of PDE is destined to be somewhat more trickier than what you've seen before in your studies. Be prepared to do some real work.

For a quick primer on PDEs, Partial Differential Equations for Scientists and Engineers (Dover Books) by Farlow is pretty good albeit somewhat shallow. Fuller undergraduate treatments can be found with:

Applied Partial Differential Equations: With Fourier Series and Boundary Value Problems by Haberman
- The best applied text at this level
Partial Differential Equation: An Introduction by Strauss
Partial Differential Equations by Fritz John
Partial Differential Equations: Theory and Technique by Carrier and Pearson
- Excellent source of insightful challenging problems

Graduate Partial Differential Equations[]

Once you have the required background in analysis, you can really study the meat of PDEs in detail with the following:

Partial Differential Equations by Jost (Strong bias for elliptic equations)
Partial Differential Equations by Evans (The standard introduction text for graduate PDEs)
Introduction to Partial Differential Equations by Folland (An more intermediate graduate level PDEs book than Evans)
Partial Differential Equations I-III by Taylor
1. Basic Theory
2. Qualitative Studies of Linear Equations
3. Nonlinear Equations

Numerical Analysis[]

Survey of Numerical Analysis

A Theoretical Introduction to Numerical Analysis by Ryaben'kii and Tsynkov
A First Course in Numerical Analysis (Dover Books) by Ralston and Rabinowitz
Functional Analysis and Numerical Mathematics by Collatz

Proofs and Mathematical Reasoning[]

True mathematics involves proofs, lots and lots of proofs (cry more physicists). The importance of mastering the art of writing valid proofs that do not make careless unstated assumptions or unproven assertions can not be understated. Oftentimes when you view some statement as initially obvious, it will turn out to be either dead wrong or at the very least hold most of the meat of the proof in proving it. Another aspect in learning proofs is following along when reading a proof in mathematical texts which requires diligently filling in all the skipped steps and checking which assumptions could be removed/weakened or what fails when they are removed/weakened. At their core, basic proofs are really easy and frequently just a matter of unwrapping the definition and following your nose, but getting into the right mindset for them might take the neophyte some practice in order to see them that way. Therefore you should work through a book or two on proofs before moving onto advanced mathematics and then blaming those books for being written badly because you lacked the prerequisite mathematical maturity from skipping this step. Some good books to learn proofs are:

A Transition to Advanced Mathematics by Smith, Eggen, and St. Andre
A Primer of Abstract Mathematics by Ash
The Foundations of Mathematics by Sibley
Mathematical Proofs: A Transition to Advanced Mathematics by Chartrand, Polimeni, and Zhang
Conjecture and Proof by Laczkovich
- An excellent supplement to any of the above books that shows a larger variety of proofs in mathematics
Proofs from THE BOOK by Aigner and Ziegler
- Not a textbook on proofs but it is an excellent collection of well done and elegant proofs to appreciate and draw inspiration from

If you find yourself struggling with proofs, then the following books provide more hand holding on the subject (but at the cost of excluding some additional material):

How to Prove It: A Structured Approach by Velleman
How to Read and Do Proofs: An Introduction to Mathematical Thought Processes by Solow
Book of Proof by Hammack

After this, set theory and mathematical logic are the logical continuation of this material and reading books on them will deepen your understand of what sets and proofs really are as well as mathematics as a whole with meta-mathematics. They also make excellent next steps in getting better at proofs and abstract mathematics in general before moving on to the much more difficult subjects like algebra and analysis. combinatorics, graph theory, linear algebra involving vector spaces, and number theory textbooks would then be the next level to practice on and are fairly easy to read at this stage of mathematical maturity.

Since you will likely find yourself revising your proofs quite often, now would be an ideal time to finally learn LaTeX (pronounced "lay-tech") to typeset your proofs and future papers in.

Set Theory, Mathematical Logic, and MetaMathematics[]

This is the formal study of the foundations of mathematics using mathematics, particularly on set theory which much of mathematics is built on and mathematical logic which studies what proofs are and the limits of what can be done. When starting in this subject the question of where to start pops up. Ideally, you would want to know a some logic while studying set theory and know some set theory while studying logic leading to a bit of a dilemma. This is solved by most introductory books giving just enough material on the other subject so you don't get lost but once you move on to intermediate and beyond books, you are assumed to have already studied both set theory and logic at least at the introductory level.

Introductory Set Theory[]

Elements of Set Theory by Enderton

Enderton is a gentle, clear, and easy to read textbook that's perfect for someone just finishing a book or course on proofs and looking for the next step to improve their math skills further. He will construct the real numbers from ZF axioms in the first five chapters.

The Joy of Sets: Fundamentals of Contemporary Set Theory by Devlin
Introduction to Set Theory by Hrbacek and Jech (baby Jech)

These books would be better for someone who already has a few proof based math courses under their belt. They're a notch harder than Enderton and go into a few more advanced topics too.

Introductory Logic[]

Introduction to Logic: and to the Methodology of Deductive Sciences (Dover Books) by Alfred Tarski
Introduction to Metamathematics by Kleene
A Mathematical Introduction to Logic by Enderton (gold standard)

Intermediate Set Theory and Logic[]

Set Theory: An Introduction to Independence Proofs by Kunen
- The newer edition is just called "Set Theory" but still is focused on independence proofs
Model Theory: An Introduction by Marker (have had a good course in algebra)
Fundamentals of Mathematical Logic by Hinman
Computability Theory by Cooper (overlaps with chapter 3 of Enderton Logic)

Advanced Computability (Recursion) Theory[]

Recursively Enumerable Sets and Degrees by Soare
Computable Structures and the Hyperarithmetical Hierarchy by Ash and Knight
Higher Recursion Theory by Sacks

Advanced Set Theory[]

Set Theory by Jech (More of a reference book)
The Higher Infinite: Large Cardinals in Set Theory from Their Beginnings by Kanamori
Constructibility by Devlin (there are errors be careful look up on SE first)^{[Free ]}
Descriptive Set Theory by Moschovakis (getting dated)

For an alternative guide through logic, consider the Teach Yourself Logic guide.

Number Theory[]

Elementary Number Theory[]

An Introduction to the Theory of Numbers by Niven, Zuckerman, and Montgomery
- This book will make you into a number theorist
An Introduction to the Theory of Numbers by Hardy and Wright
Elementary Number Theory (Dover Books) by Dudley
Number Theory (Dover Books) by Andrews
- The first half is a combinatorial approach to basic number theory followed by an introduction to combinatorial number theory by a pioneer in the field

Algebraic Number Theory[]

A Classical Introduction to Modern Number Theory by Ireland and Rosen
- A bit harder than the above, the go-to book after you've taken undergrad abstract algebra
- Starts off with elementary number theory
A Course in Arithmetic by Serre (first half; much harder than the above)
Primes of the Form x²+ny²: Fermat, Class Field Theory, and Complex Multiplication by Cox
Algebraic Number Theory and Fermat's Last Theorem by Ian Stewart and Tall
Number Theory 1-3 by Kazuya Kato, Nobushige Kurokawa, and Takeshi Saito
1. Fermat's Dream
2. Introduction to Class Field Theory
3. Iwasawa Theory and Modular Forms
Algebraic Number Theory by Cassels and Fröhlich
Algebraic Number Theory by Neukirch and Schappacher

Analytic Number Theory[]

Introduction to Analytic Number Theory by Apostol
A Course in Arithmetic by Serre (second half)
Modular Functions and Dirichlet Series in Number Theory by Apostol
Multiplicative Number Theory by Davenport
Multiplicative Number Theory I: Classical Theory by Montgomery and Vaughan
Analytic Number Theory by Iwaniec and Kowalski (The reference)

Computational Number Theory[]

A Computational Introduction to Number Theory and Algebra by Shoup
Prime Numbers: A Computational Perspective by Crandall and Pomerance
Algorithmic Number Theory: Lattices, Number Fields, Curves and Cryptography by Buhler and Stevenhagen
A Course in Computational Algebraic Number Theory by Cohen
Advanced Topics in Computational Number Theory by Cohen

Elliptic Curves[]

Rational Points on Elliptic Curves by Silverman and Tate
The Arithmetic of Elliptic Curves by Silverman
Advanced Topics in the Arithmetic of Elliptic Curves by Silverman

Probability and Randomness[]

Probability (Multivariable Calculus based)[]

Introduction to Probability by Bertsekas and Tsitsiklis
Introduction to Probability by Blitzstein and Hwang
First Course in Probability by Ross
Introduction to Probability Theory by Hoel, Port, and Stone
The Probability Tutoring Book: An Intuitive Course for Engineers and Scientists (and Everyone Else!) by Ash

Stochastic Processes[]

Introduction to Stochastic Processes by Hoel, Port, and Stone
Introduction to Probability Models by Ross
Stochastic Processes by Ross
A First Course in Stochastic Processes by Karlin and Taylor
A Second Course in Stochastic Processes by Karlin and Taylor
Probability and Random Processes by Grimmett and Stirzaker
Stochastic Processes in Physics and Chemistry by Van Kampen

Mathematical Statistics[]

See the universal recommendations on Statistics.

Design of Experiments[]

See the universal recommendations on Design of Experiments.

Measure Theoretic Probability Theory[]

Probability with Martingales by David Williams
Probability and Measure by Billingsley
An Introduction to Probability Theory and Its Applications Vol. 2 by Feller
Probability Theory: A Comprehensive Course by Klenke
Probability-1 by Shiryaev

Stochastic Calculus[]

Stochastic Differential Equations: An Introduction with Applications by Bernt Øksendal
Diffusions, Markov Processes and Martingales: Volumes 1 and 2 by Rogers and Williams
1. Foundations
2. Itô Calculus
Brownian Motion and Stochastic Calculus by Ioannis Karatzas and Steven Shreve

Combinatorics and Graph Theory[]

Primers in Combinatorics and Graph Theory[]

These 2 books are aimed at high school students with knowledge of elementary algebra to give them a taste of pure mathematics.

Mathematics of Choice: Or, How to Count Without Counting by Ivan Niven
Introduction to Graph Theory (Dover Books) by Trudeau

Introduction to Combinatorics[]

Combinatorics: Topics, Techniques, Algorithms by Cameron ^[Website]
A Walk Through Combinatorics: An Introduction to Enumeration and Graph Theory by Miklós Bóna
A Course in Combinatorics by van Lint and Wilson

Introduction to Graph Theory[]

Graph Theory by Diestel
Modern Graph Theory by Bollobas

Enumerative Combinatorics[]

A Course in Enumeration by Aigner
Enumerative Combinatorics: Volumes 1 & 2 by Stanley ^[Website]

Extremal Combinatorics and Graph Theory[]

Extremal Combinatorics: With Applications in Computer Science by Jukna ^[Website]
Extremal Graph Theory (Dover Books) by Bollobas
The Probabilistic Method by Alon and Spencer

Algebraic Graph Theory[]

Algebraic Graph Theory by Biggs
Algebraic Graph Theory by Godsil and Royle ^[Website]

Linear Algebraic Graph Theory[]

Graphs and Matrices by Bapat
Graph Spectra by Brouwer and Haemers ^[Draft]
An Introduction to the Theory of Graph Spectra by Cvetković, Rowlinson, and Simić

See also Combinatorial Optimization & Network Flows and Combinatorial Game Theory on the CS&E page.

Abstract Algebra[]

Abstract algebra (also called modern algebra or just algebra) is the study of mathematical structures that consist of a set with algebraic rules defined on the set's elements. This enables us to prove general results that depend only on the particular rules the structures have and not a particular example structure (like the rationals, reals, quaternions, polynomials, matrices, or integers modulo n) we have in mind that satisfies those rules.

Abstract algebra is not to be mistaken with "college algebra" as that refers to the elementary algebra which is typically done in grade school. It's called "college algebra" because, well, nobody would pay for a course called The Algebra You Should Have Learned in High School But Were Too Much Of A Fuck Up To Do So. If you're looking for resources on that, see the Precalculus section above.

Group Theory Teaser[]

These books are accessible enough to give freshmen or high school students a digestible taste of abstract math and build intuition for when they later get to algebra

Groups and Their Graphs by Grossman and Magnus (sadly out of print)
Visual Group Theory by Carter
Groups and Symmetry by Armstrong

Undergraduate Algebra[]

Algebra by Artin
Topics in Algebra by Herstein
- Herstein's Abstract Algebra is an abbreviated version of his Topics for a one semester course
- Terminology is slightly old-fashioned
Abstract Algebra by Dummit and Foote (more of an encyclopedic reference than a book)
Algebra by Mac Lane and Birkhoff
Abstract Algebra by Grillet
A Course in Algebra by Vinberg
- Similar to Artin but friendlier overall
- Technically a graduate book but its level is closer to undergrad
Undergraduate Algebra: A Unified Approach by Brešar

Herstein's Topics takes a fairly conventional approach to the subject while Artin's book does things in a rather unique and geometrical way. While both are well written texts on their own, but pairing them is very useful.

Survey of Abstract Algebra Applications[]

Abstract Algebra: Theory and Application by Tom Judson
- Also covers the theory; a good general introduction
Applied Abstract Algebra by Lidl and Pilz
Applications of Abstract Algebra with Maple and Matlab by Klima, Sigmon, and Stitzinger
Topics in Applied Abstract Algebra by Nagpaul and Jain

Matrix Groups[]

Matrix Groups for Undergraduates by Tapp
Naive Lie Theory by Stillwell

Graduate Algebra[]

Basic Algebra I & II (Dover Books) by Jacobson
- Vol I is closer to 1st year books in terms of level
Algebra: Chapter 0 by Aluffi
- Can be used as a first introduction as well
Algebra by Hungerford
- Don't mistake it for his Abstract Algebra which is at a lower level
Algebra by Lang ^{[A Companion to Lang's Algebra]}

Commutative Algebra[]

Introduction to Commutative Algebra by Atiyah and Macdonald
Basic Commutative Algebra by Singh
A Term of Commutative Algebra by Altman and Kleiman
Commutative Algebra with a View Towards Algebraic Geometry by Eisenbud

Group Theory[]

An Introduction to the Theory of Groups by Rotman
Finite Group Theory by Isaacs
A Course in the Theory of Groups by Robinson

Noncommutative Rings[]

Noncommutative Rings by Herstein
A First Course in Noncommutative Rings by Tsit-Yuen Lam
Exercises in Classical Ring Theory by Tsit-Yuen Lam
- Solutions and commentary to the above
Lectures on Modules and Rings by Tsit-Yuen Lam
- Sequel to First Course in Noncommutative Rings but independent

Exercises in Modules and Rings by Tsit-Yuen Lam
- Solutions to the above

Analysis[]

The origins of mathematical analysis are found in the age old struggle of mathematicians to deal with the infinite and infinitesimal dating all the way back to antiquity with the works of Eudoxus of Cnidus and Archimedes of Syracuse. With the piecemeal development of calculus by Cavalieri, Pascal, Fermat, Descarte, Leibniz, Euler, Lagrange, Fourier and many others, calculus gradually showed itself to be a powerful yet deeply troubled tool. As much as mathematicians tried, they struggled with clearly defining key stumbling points: the concept of an infinitesimal number smaller than 1/n for all integers n yet nonzero in a logically consistent manner, the concept of infinite approach, division by 0, and the rules in which an infinite series may be manipulated and examined. These were not just pointless trifles that could be brushed off as more philosophy than math but of increasing practical importance. As time went on, many counterexamples (and not just pathological ones) where the naive application of the methods of calculus would produce erroneous results cast a shadow on the validity of all other results of calculus. Many critics wanted to end its study altogether and relentlessly mocked the concept of infinitesimals as "the ghosts of departed quantities". Since the triumphs for calculus were both numerous and far reaching, mathematicians strongly sought to make the results of calculus proven rather than discarding the subject all together. This situation was finally resolved only in the early 19th century with the work of Cauchy and Weierstrass and the ε-δ definition of a limit (which would ironically kill off infinitesimals until the 1960s and the advent nonstandard analysis) that birthed the new field of analysis. This sparked off a massive revolution in mathematics and the field of analysis quickly exploded into various distinct but interconnected directions.

Students just finishing the study of calculus and basic proofs often fail to realize the sheer importance of careful work in analysis and scoff the whole subject off as merely "intellectual or autistic masturbation". This mentality comes from being coddled with the toy-problems you see in calculus that are selected to hide any possible nastiness that comes from complicated situations that frequently arise in science and engineering. Even if the student is aware of the importance of being careful, they are often insulted when forced to work through "obvious" theorems. The problem here is that many results in analysis that seem obvious are frankly very difficult to prove (for example see the Jordan curve theorem) or even dead wrong. In order to gain the ability to prove important and powerful theorems hidden away in analysis, students need plenty of practice working through basic problems to gain familiarity and mathematical maturity to move on to difficult work even if this means you need to spend time proving that "every open ball is open".

A good reference to keep with you and refer to often is Counterexamples in Analysis by Gelbaum and Olmsted published by Dover Books.

Inequalities[]

A lot of the exercises in analysis often boil down to spamming the triangle inequality until you get the result you want. If you haven't done much work with inequalities since grade school, practicing them can make the subject seem vastly easier.

The Cauchy-Schwarz Master Class: An Introduction to the Art of Mathematical Inequalities by Steele
Inequalities by Hardy, Littlewood, and Polya

Real Analysis (Metric Space based)[]

This is where the results of single variable calculus are finally made both rigorous and generalized.

The gold standard for the subject is the first 8 chapters of Rudin's Principles of Mathematical Analysis whose slick proofs and challenging exercises can't be beat. Chapters 9 and 10 of Rudin on multivariable analysis are bit sparse to learn from so you're better off moving fuller treatment on analysis on manifolds (see below) to learn from. The final chapter 11 is completely skippable as other books are far better in their treatment of Lebesgue integrals/measure theory than Rudin's brief survey. Apostol's Mathematical Analysis goes through a bit more material than Rudin, gives more worked out proofs, and has relatively easier problems. If you're struggling with Rudin, give Abbott or Apostol a try. Zorich's Mathematical Analysis I & II starts lower level than Rudin but ends on much higher level covering many additional topics including manifolds. The price paid is that his books is quite longer than Rudin and larger time investment.

A more classical treatment of analysis, but starting from the Lebesgue integral is An Introduction to Classical Real Analysis by Hewitt and Stromberg. This book is like how analysis was done a hundred years ago but with a more sophisticated integral.

Another alternative treatment that you could read afterwards is Sternberg and Loomis' Advanced Calculus . Differentiation is done on normed vector spaces, and integration is done using the theory of content; multivariable stuff is done via manifolds. It also covers some physics. Its abstract approach makes it more challenging than the other books.

Analysis on Manifolds[]

This is the study of analysis on multidimensional spaces making multivariate and vector calculus rigorous and pushing the subject further. A good grounding in linear algebra is required. Going to a book like Tu's Manifolds instead of one of the below can also be viable.

Munkres' Analysis on Manifolds
Spivak's Calculus on Manifolds
do Carmo's Differential Forms and Applications

Fourier Analysis[]

Fourier Series (Dover) by Tolstov
Fourier Analysis: An Introduction by Stein & Shakarchi
Fourier Analysis and its Applications by Folland
Fourier Analysis by Körner
Fourier Series and Integrals by Dym and McKean

Complex Analysis[]

Complex Analysis by Stein & Shakarchi
Complex Analysis^{[website][guide]}' by Gamelin
Functions of One Complex Variable by Conway
Complex Analysis by Ahlfors
Visual Complex Functions: An Introduction With Phase Portraits by Wegert
Complex Analysis by Serge Lang
- Also check out the solutions guide by Shakarchi
Complex Analysis in One Variable by Narasimhan (advanced)

Graduate Real Analysis[]

Real Analysis: Measure Theory, Integration, and Hilbert Spaces by Stein & Shakarchi
Real Analysis by Royden
Real Analysis: Modern Techniques and Their Applications by Folland
Real and Complex Analysis by Rudin
Real Analysis by Loeb (also includes some nonstandard analysis)
Introduction to Modern Analysis by Kantorovitz (very broad)

Functional Analysis[]

Introduction to Topology and Modern Analysis by George Simmons (very few prerequisites)
Functional Analysis: Introduction to Further Topics in Analysis by Stein & Shakarchi
Functional Analysis by Lax
- Includes several historic notes of the subject and the fate of its researchers during WWII
Functional Analysis by Rudin
Linear Operators, 3 Volume Set by Nelson Dunford & Jacob T. Schwartz

Abstract Harmonic Analysis[]

Introduction to Abstract Harmonic Analysis (Dover Books) Loomis
Fourier Analysis on Groups (Dover Books) by Walter Rudin
A Course in Abstract Harmonic Analysis by Folland

Nonstandard Analysis[]

Nonstandard Analysis (Dover Books) by Robert
Applied Nonstandard Analysis (Dover Books) by Martin Davis
Nonstandard Analysis: Theory and Applications by Arkeryd, Cutland and Henson
Real Analysis Through Modern Infinitesimals by Nader Vakil (suitable for undergraduates)
Lectures on the Hyperreals: An Introduction to Nonstandard Analysis by Goldblatt
Nonstandard Analysis for the Working Mathematician by Loeb and Wolff
Nonstandard Methods in Stochastic Analysis and Mathematical Physics (Dover Books) by Albeverio, Hoegh-Krohn, Fenstad, and Lindstrom
Non-standard Analysis by Abraham Robinson (The original book on the subject)

Sets of Books on Analysis[]

Because of how broad and how essential the subject of analysis is, there are quite a few series of volumes that attempt to guide the reader through the landscape. Not all of these books necessary form a series, but they do form a logical grouping by the same authors.

As mentioned before: Baby, Papa/Big, and Grandpa Rudin.

Principles of Mathematical Analysis
Real and Complex Analysis
Functional Analysis

The most well-known series in analysis is the Princeton Lectures in Analysis by Stein and Shakarchi.

Fourier Analysis: An Introduction
Complex Analysis
Real Analysis: Measure Theory, Integration, and Hilbert Spaces
Functional Analysis: Introduction to Further Topics in Analysis

Terence Tao has also written quite extensively on introductory analysis.

Analysis I
Analysis II
An Introduction to Measure Theory

As mentioned, Zorich's books only come in two volumes, but they cover a lot.

Mathematical Analysis I
- Sets, real numbers, limits, continuous functions
- Differential calculus in one and several variables
- Riemann integration
Mathematical Analysis II
- Metric and topological Spaces
- Differential calculus on normed vector spaces
- Multiple integrals
- Differential Forms and integration
- Classical vector analysis and physics
- Fourier Analysis

Amann and Escher treat introductory analysis from a highly abstract point of view. Commutative diagrams galore. Only for the daring or the prepared.

Analysis I
- Sets and logic, abstract algebra, linear algebra, real and complex numbers
- Convergence, Banach spaces, series
- Topology
- Differential calculus
- and more
Analysis II
- Integration with Banach spaces
- Differential calculus and an introduction to manifolds
- Complex analysis with Pfaff forms
Analysis III
- Measure theory and integration
  - includes Bochner-Lebesgue integral
- Differentiation on manifolds
  - with some Riemannian geometry
- Integration on manifolds

Knapp (free)

Basic Real Analysis
Advanced Real Analysis

Comprehensive Course in Analysis by Barry Simon

Real Analysis
Complex Analysis 2A and 2B
1. Basic Complex Analysis
2. Advanced Complex Analysis
Harmonic Analysis
Operator Theory

Topology[]

Point-set Topology[]

Topology by James Munkres (The standard for most topology courses)
Introduction to Topological Manifolds by John Lee
Elementary Topology (Dover Books) by Michael Gemignani
General Topology (Dover Books) by Stephen Willard (A bit more difficult than the above)

A great supplement to any General Topology book is Counterexamples in Topology (Dover Books) by Steen and Seebach. See also Pi-Base, which is a digital, searchable version with more counterexamples.

Algebraic Topology[]

Algebraic Topology by Hatcher
Differential Forms in Algebraic Topology by Bott and Tu
An Introduction to Algebraic Topology by Rotman
A Concise Course in Algebraic Topology by May (Advanced)

Differential Topology[]

Topology from the Differential Viewpoint by Milnor (very short)
Introduction to Differential Topology by Bröcker and Jänich
Differential Topology by Victor Guillemin and Alan Pollack
Differential Topology by Hirsch (More advanced)

Geometric Topology[]

Low-Dimensional Topology[]

Low-Dimensional Geometry: From Euclidean Surfaces to Hyperbolic Knots by Francis Bonahon (elementary presentation)
Three-Dimensional Geometry and Topology by Thurston and Levy

Knot Theory[]

Knot Theory by Livingston (Primer)
Knots and Physics; On Knots; Formal Knot Theory (Dover Books) by Kauffman
An Introduction to Knot Theory by Lickorish
Knots and Links by Rolfsen
Knot Theory and Its Applications; A Study of Braids by Kunio Murasugi
Knots, Links, Braids and 3-Manifolds: An Introduction to the New Invariants in Low-Dimensional Topology by Prasolov and Sossinsky

Geometry[]

Classical Geometries[]

Geometry by Its History by Ostermann and Wanner
- From the Babylonians up to the 20th century
Geometry: Euclid and Beyond by Hartshorne
- Supplementary text to Euclid
Non-Euclidean Geometry by Coxeter
Geometry by Audin
- Transformation geometry
- Projective geometry
- Envelopes and evolutes
- Touches on curves and surfaces
Geometry with an Introduction to Cosmic Topology by Hitchman
Geometries by A. B. Sossinsky
Introduction to Classical Geometries by Galarza and Seade

Geometry From a Differentiable Viewpoint by McCleary
- Also covers geometry of curves and surfaces and touches on manifolds. The book of P.M.H. Wilson is similar

Gibson's Trilogy
1. Elementary Euclidean Geometry: An Undergraduate Introduction
2. Elementary Geometry of Differentiable Curves: An Undergraduate Introduction
3. Elementary Geometry of Algebraic Curves: An Undergraduate Introduction
Borceux's Trilogy
1. An Axiomatic Approach to Geometry
2. An Algebraic Approach to Geometry
3. A Differential Approach to Geometry
Geometry I and II by Berger (more advanced)

Modern Differential Geometry[]

Smooth Manifolds[]

Introduction to Smooth Manifolds by John Lee
An Introduction to Manifolds by Loring W. Tu
A Short Course in Differential Geometry and Topology by Fomenko and Mishchenko
A Comprehensive Introduction to Differential Geometry, Volume 1 by Spivak

Riemannian Geometry[]

Riemannian Geometry by do Carmo
Riemannian Manifolds: An Introduction to Curvature by John Lee
Introduction to Riemannian Manifolds by John Lee
Differential Geometry: Connections, Curvature, and Characteristic Classes by Loring Tu
Riemannian Geometry and Geometric Analysis by Jost

Synthetic Differential Geometry[]

This is a reformulation of differential geometry, but with a foundation in category and topos theory. Do note that the law of the excluded middle does not hold in this theory.

Synthetic Geometry of Manifolds by Anders Kock
Basic Concepts of Synthetic Differential Geometry by René Lavendhomme
Synthetic Differential Geometry by Anders Kock

Smooth infinitesimal analysis is analysis with a similar foundation.

A Primer of Infinitesimal Analysis by John L. Bell
Models for Smooth Infinitesimal Analysis by Ieke Moerdijk and Gonzalo E. Reyes

Algebraic Geometry[]

Overview[]

An Invitation to Algebraic Geometry by Karen Smith, Lauri Kahanpää, Pekka Kekäläinen, and William Traves

Introductory Algebraic Geometry without Schemes[]

Lectures on Curves, Surfaces and Projective Varieties by Beltrametti et al.
Algebraic Geometry: A Problem-Solving Approach by Garrity et al.
Basic Algebraic Geometry 1: Varieties in Projective Space by Shafarevich
Algebraic Geometry, A First Course by Harris
Algebraic Geometry I: Complex Projective Varieties by Mumford

With Schemes[]

A Royal Road to Algebraic Geometry by Holme
Algebraic Geometry I: Schemes, With Examples and Exercises by Görtz and Wedhorn
Foundations of Algebraic Geometry by Vakil
The Geometry of Schemes (Graduate Texts in Mathematics) by Harris and Eisenbud
Algebraic Geometry and Commutative Algebra by Bosch (CA+AG in one book!)
Introduction to the Theory of Schemes by Manin and Leitis
Basic Algebraic Geometry 2: Schemes and Complex Manifolds by Shafarevich
3264 and All That: A Second Course in Algebraic Geometry by Harris and Eisenbud
Algebraic Geometry II by Mumford