Ask HN: Which books in your field do you think are perfect for self study?

101 points by debanjan16 ↗ HN
In almost every field there are encyclopedic reference books which are for experienced people to look up stuff when needed.

Then there are books with wonderful prose that are suitable for self learners that want to learn the topic for the first time.

Can you name some books of the second type in your field of study?

24 comments

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Code: The Hidden Language of Computer Hardware and Software

By Charles Petzold.

Perfect intro for a layman getting into Computer Architecture

The MIDI Files by Rob Young. "a comprehensive, easy-to-read reference package covering everything you ever wanted to know about MIDI."
Noam Nisan and Shimon Schocken's The Elements of Computing Systems good starting point for various topics - It's the accompanying book to their Nand2Tetris course and, along with my explorations with the Raspberry Pi, was one of the starting points in my computing exploration.
Richard Hamming’s “Methods of Mathematics Applied to Calculus, Probability, and Statistics” is a wonderful introduction to calculus from one of those rare individuals who mastered the interplay between applications of mathematics and its theory. It’s packed with insights from a true veteran. He aims to teach you to view and interact with mathematics as a living, breathing, occasionally messy but beautiful thing; and in my opinion he manages to do so with a rare humanity.

He was one of the gems of mathematical exposition. If you’ve studied any information theory you probably know his surname well. His other books are also excellent.

It begins with a lovely quotation: “every scientist owes a labour of love to his field”. His work embodies that. There are lots of exercises, and it includes answers to enough of them for you to check you’re on the right track.

Equally "The Art of Doing Science and Engineering" by Hamming is one of the best books around on the philosophy of problem solving, and an excellent primer on core concepts in signals processing, information theory, and computing.
Do you have a similar book to study for "Highschool maths" before starting this one?
The Art of Problem Solving books are great and have complete solution manuals available as well.
Design Pattern : Head first design patterns (eric freedman, kathy sierra, et al)

Communication : Pyramid Principle (barbara minto)

Definitely not in compiler field (and actually makes my recommendations more legit as field professionals tend to overestimate other people's ability to learn), but can recommend three books, ordered by difficulty asc:

Writing interpreters and compilers for the raspberry pi using python by Anthony J.Dos Reis

Crafting Interpreters by Nystrom

Game Scripting Mastery (Forgot the author and too lazy to Google)

People recommended books a lot for some reason when I was starting out programming. I tried them once or twice and it they just didn't work for me. Instead I just followed random internet guides and asked questions in IRC, then eventually went to college. All worked out.

I think a good self learner will just find what works for them on Google, not that that can't be books for some people.

I have almost the exact opposite experience: tried asking dumb questions on IRC a lot, until I realized going to the source (books!) is the way to learn.
It depends.

I learned programming by myself reading from the internet and some books that were not very good (actually simply bad but the most popular in my country), then I went to college and read specific books and got to learn from some of the teachers that actually programmed for a living and realized that I had holes the size of the mariana trench in my knowledge.

There are two out-of-field books that I always recommend to policy analysts, economists, and regulatory drafters: The Design of Everyday Things by Don Norman, and Algorithms To Live By by Brian Christian and Thomas Griffiths. Both are high signal-to-noise primers on topics that are relevant in decision making and policy, but are rarely covered in an economics or public policy curriculum.
Intro Data Science :

Introduction to statistical learning from Hastie, et all. Generously hosted for free by the authors here.

https://www.statlearning.com/

This is an amazing book. It explains concepts like the bias-variance tradeoff more clearly than anything else I've read on data science.