For math I have some stuff I had my old tutor recommended me.
Undergraduate Core:
A Concise Introduction to Pure Mathematics (Martin Liebeck) -
Analysis I (Terrence Tao) -
Linear Algebra Done Right (Axler)
A Book of Abstract Algebra (Pinter)
Introduction to Metric & Topological Spaces (Sutherland)
Analysis II (Terrence Tao)
Princeton Lectures Book 2 - Complex Analysis (Stein & Shakarchi)
Undergrad Extras:
An Infinitely Large Napkin (Evan Chen) - A rapid introduction to many fields of math at the undergraduate and graduate level. Heavily recommend supplementing the undergrad core reading with this.
An Invitation to Ergodic Theory (Silva) -
A sampling of Remarkable Groups (Bonanone et al.) -
Lectures on Fractal Geometry and Dynamical Systems (Pesin and Climenhaga) -
Geometric Group Theory (Loh) - An introduction to the study of groups using geometric/metric techniques.
The Knot Book (Colins) - A very informal introduction to knot theory.
Ramsey Theory on the Integers (Landman and Robertson)
Graduate Core:
Algebra Ch. 0 (Aluffi) - Graduate level Algebra.
An introduction to Measure Theory (Tao) or Measure Theory, Integration and Hilbert spaces (Stein and Shakarchi) - Graduate level real analysis, part 1.
An Epsilon of Room (Tao) - Graduate level real analysis part 2. Includes more on measures and some functional analysis.
Vector Analysis (Janich) or An introduction to manifolds (Tu) - Smooth manifolds.
Linear Analysis (Bella Bollobas) - Functional analysis.
Algebraic Topology (Munkres)
Topology from the Differentiable Viewpoint (Milnor) - Differential topology.
Graduate Extras:
Probability Essentials (Jacod & Protter) - Has measure theory as a prerequisite.
Brownian Motion, Martingales and Stochastic Calculus (Le Gall) - Stochastic processes & calculus. Has measure theoretic probability and functional analysis as a prerequisite.
Princeton Lectures Book 1 and 4 (Stein & Shakarchi) - 1 covers
Introduction to Dynamical Systems (Brin and Stuck) - General overview of dynamical systems, highly recommended.
Introduction to the Modern Theory of Dynamical Systems (Katok Hasselblatt) - Super in depth treatment of dynamical systems, good follow up to the above.
Introduction to 3-Manifolds (Jennifer Schultens) -
Introduction to Riemannian Geometry (Lee) -
An Introduction to Lie Groups and the Geometry of Homogeneous Spaces (Arvanitoyeorgos) - Lie theory.
Measure Theory and Fine Properties of Functions (Evans & Gariepy) -
Ergodic Theory with a view towards Number theory (Ward) -
Morse Theory (Milnor)
Differential Forms in Algebraic Topology (Bott and Tu)
For CHEMISTRY
A Primer of Drug Action, R.M. Julien, 13th ed., by Claire D. Advokat
Katzung, Bertram G., Masters, Susan B., and Trevor, Anthony J. Basic & Clinical Pharmacology, 12th edition. McGraw-Hill Profess. .
Undergraduate
Organic: Organic Chemistry as a Second Language, The art of writing reasonable organic reaction mechanisms
Inorganic: Inorganic Chemistry, Molecular Symmetry and Group Theory
Analytical: Principles of Instrumental Anlsysis, Fundamentals of Analytical Chemistry
Graduate
Organic: Advanced Practical Organic Chemistry, March's Advanced Organic Chemistry, Greene's Protective Groups in Organic Synthesis, Purification of Laboratory Chemicals, Strategic Applications of Named Reactions in Organic Synthesis
Inorganic: Advanced Inorganic Chemistry.
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!codecels r8 my list
Programming/Software Engineering:
Automate the Boring Stuff with Python
Structure and Interpretation of Computer Programs
Software Design for Flexiblity
How to Design Programs (Never read this one, but heard it was good)
Specific Programming Languages
Practical Common Lisp
Real World OCaml
The Little Schemer
Learn You a Haskell
JavaScript: The Good Parts
Programming Language Implementation
Lisp In Small Pieces
Crafting Interpreters
Modern Compiler Implementation in ML
Engineering a Compiler
The Elements of Computing Systems
Programming Language Theory
The Little Typer
The Power of Prolog
The Reasoned Schemer
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Not a fan of this book. Not practical enough for complete beginners to haskell (it's a lot of simple exercises) and not deep enough for anyone who knows what a functor is.
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People aren't learning Haskell as a 'get shit done' language - it should be about showing off the strong points of the language, which is its concision and new way of thinking. If you know what a functor is before you read it then the book's not for you
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!codecels amiright or amiright
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u right
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I don't really mind Javascript but I have had moments where I understand why people seethe at it.
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I love JavaScript, causes so much seethe, I use it for all my scripting cause it's easier to write than python.
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I use Jython
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just use java
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no, Jython causes seethe w/ the name alone.
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Java is for cute twinks
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Even though it gets literally everything else wrong, JS was still the first popular language to implement closures.
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I use Node/JS for this
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He fell for the meme
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Is Haskell in general a meme or just that book? IMO learning Haskell is worth it just for using at job interviews to intimidate potential employers
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generallly speaking just a meme, its not really used in the grand scheme even though its heavily advocated by fp fans
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discarded
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I agree with this list
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Seconded
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You remind me of my friendly neighborhood sysadmin neurodivergent. That you, Kyle?
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