Ask HN: Which books do you consider real gems in your field of work/study?

[curious16]

Well written books can serve as eye openers and warp your understanding of a topic when read at the correct time in your life.

Can you name a few books of that type that really were of such high value in your field of work or study?

[kristiandupont]

I am going to repeat what I always say when these book threads come up:

I love all the recommendations here but please say a word or two about why you recommend said books. Sell them to me, don't make me do the work. Dumb lists of titles are so uninteresting.

[dxbydt]

> why you recommend said books. > Sell them to me

ok, i will try.

2 books I absolutely love and have read cover to cover several times, solved most of the 1000+ problems.

1. Inference - Rohatgi

2. Inference - Stapleton

Why I recommend them ? The real answer is super long. But the short version is - there are thinkers & there are doers. Basically, the mathematical statistics world has these theory-building Bourbaki type guys who write a LOT, say a LOT, but never get to the fucking point (imho). The opposite view is "math is bunch of tricks. its like chess - more middlegames & endgames you know, higher chance of winning. No real point in learning who originally came up with this particular middle game variation, or why does this opening work etc etc. Just learn the trick & play the game." So that's the eastern (Indian/Chinese) school of thought, which is what I subscribe to.

The 2 inference books listed above are essentially grab-bags of tricks. Do this - it works - now try it on these problems - ok next trick...on & on. So I solved the 1000+ problems & now I know lots of these methods that just work.

eg. recently i was asked - some vc's are evaluating a startup. their valuations are $1 million, $4 M,$10M, $20M, $50M. what's your evaluation & why ?

so i'm thinking - hey isn't this just rohatgi taxicar ? so i quickly said- sum is 85, times 1/5 is 17. Whereas largest observed is 50, times 6/5 is 60, so half is 30. since 50 was max observed, another estimator is half that, ie. 25. if you want doctor's estimate, get rid of 1 and 50, then sum is 34 so times 1/3 is 11.3

so then we have 4 estimators, - the sample mean is 17 million, its the method of moments estimator, clearly unbiased but high mean square error because variance is high. the maximum likelihood estimator is 25 mil, and has smallest variance, but the mse will not be the lowest since it is not unbiased so bias square will add. the 30 mil estimate is also unbiased, but has low variance so it has the lowest mse of the lot. the doctor estimator 11 million is unbiased but high variance and mse is in between. now if you want the absolute lowest mse, i can cook up a 5th estimator which has nonzero bias but mse will be the minimum....

at this point the interviewer interrupts me - you've never seen this problem because we came up with it in our last meeting at our firm. Yet you gave me 4 very good estimators under 2 minutes & want to cook up a 5th one that's even better. And you don't even have a phd. meanwhile i just spoke to an actual phd and asked him this same question, he went on and on for 20 minutes without giving me a single concrete estimator!

so that's the thing. rohatgi, stapleton, these are about real world, down & dirty, how to do stuff. how to solve actual problems.

whereas the gelman bda, the shao, the schervish, the lehman, the bickel & doksum - these were my prescribed textbooks. imho they are absolute garbage, worse than dirt. after the exam i threw them away. such bullcrap. they go on & on without getting anywhere & have practically zero good worked examples.

so that's my 2 cents. i still have the rohatgi & stapleton on my desk. sometimes i tear up when i look at them. they have taught me so, so much!

[justin66]

> Dumb lists of titles are so uninteresting.

The most information-dense form of book recommendation possible is probably a “dumb” list consisting largely of books one knows and appreciates, with one or two new titles in addition. I’ll probably learn more about where a person recommending a book I haven’t read is coming from based on a list of their favorites than I will from the text of a hastily constructed review.

In any case, I wouldn’t dismiss someone out of hand for providing a “dumb” list.

[fuzzfactor]

In my line of work it's the Annual Book of ASTM Standards.

In particular the handful of volumes that pertain to my established laboratory & field work, as well as possible aspirational efforts.

It can really pay to keep up to date.

Also, the text/content of all the standards are the work of volunteer technical people, who come to complete consensus before the well-paid journalist professionals at the nonprofit publisher send it to press.

ASTM may contain some of the most statistically documented laboratory procedures for repeatabiliy & reproducibility compared to what you normally find.

A lot of the books people have commented on have been influential in the past and do stand on their own today.

Well even though outdated ASTM standards may have limited value, one real offsetting benefit is the past experience of using them in previous years when they were current and some standards were less fully developed.

So if you think about it, the current year's publication is a snapshot, the majority of your collection from previous years is huge by comparison, and ends up proportionally more helpful on the whole, even though somewhat outdated or even obsolete.

And these books are hefty, they weigh kilos per year and cost the big bucks.

Not really worth it either unless you're really ready to dip deeply into the unique type of bureaucracy associated with these type of efforts.

But it gets much worse, you think ASTM books are boring, how about the Federal Register?

There's another ongoing publication where the bureaucracy is so thick, someone can specialize so highly at navigating it that they can more effectively win bids without any technical qualifications compared to actual practicioners, most of whom don't stand a chance on merit alone. Not for me, but if you're aiming for Uncle Sam's pocketbook you need to up your game here.

I guess there are a lot of other books which might inspire people to take some action of their own, or even build a business around. Not always ones that are intended to be inspirational either.

Some people think Buckminster Fuller was inspirational, one of my handful of books when I had a shelf is Earth, Inc.

Title sounds almost like the name of a business or something:

https://books.google.ca/books?id=l5DODQAAQBAJ&pg=PP5&source=...

Only about a half inch thick, fits on any shelf with ease, not for people that dislike big words. You have been warned.

Then for electronics it's Radiotron. Specifically RDH4:

https://archive.org/details/bitsavers_rcaRadiotr1954_9495850...

Not so thin, 1523 pages mainly for people that do really like equations.

If you can build projects like they have here, I guarantee you will be able to do things your peers will not.

Both published decades ago, so it's up to the reader to fill in the blanks about how we got to where we are now.

[da4id]

How to measure anything. I think it's targeted for actuaries/insurance, though I'm not in that field. But it did change my idea of what can be analyzed and measured. The beginning is repetitive. Some of it is very unorthodox. But it was very useful in detailing how to evaluate risk.

How to talk to little kids so little kids will listen. I don't have kids and read it on a whim. I've found it's excellent for communicating with people in general during conflict (especially patients). The author is a counsellor and describes real counselling sessions with parents who want better relationships with their children. I enjoyed how the author uses the same techniques on the adults and obtains the same manner of response as when used on the kids.

Understanding Complexity is not a book but a part of the Great Courses. It's hard to say what it directly changed but it did affect how I view everyday life, from traffic to physiology.

Hui's Approach to Internal Medicine was very helpful for transitioning from knowing about medical facts to practical medical knowledge useful to everyday care. It's focus is on 'approach' rather than facts. It has a practical approach to medical issues. First distinguishing by ones in the same category of pathophysiology then practical approach to distinguishing issues within the category. It's a dense book but an excellent read and a good reference.

[bmitc]

> How to measure anything.

I think I found out about this book from Hacker News. I haven't gotten to it yet, but I need to. Seems very unique.

[mikehollinger]

Engineer turned engineering leader here.

"Good Strategy / Bad Strategy" by Richard Rumelt - An awesome book on strategy, which explains very plainly how to construct a reasonable strategy, and see signs of bad strategy. It (among other things) dissects NVIDIA's rise in the late 2000's, and predicts (more or less) the next ten years of where the company went.

"The Effective Manager" by Mark Horstman - All the things that no one says or tells about management and communication.

"Team Topologies" by Skelton and Pais - A really good view of organizational design patterns and anti-patterns for software teams rooted in the premise of Conway's Law.

[argggg]

Second "The Effective Manager", that's one of the best management books I have ever read - and one of the very few totally practical ones. It also gave me a significant head start in managerial life because most of the people above me have no idea how to do any of the things clearly laid out in this book.

[docdocgoose]

Principles of Neural Science by Kandel et al

Molecular Biology of The Cell by Alberts et al

Janeway’s Immunobiology

Robbin’s Pathologic Basis of Disease

All of these books are extraordinary in their sheer ability to organize thousands of small details into thematic narratives of how life operates.

They also reveal how hard we humans try to narrate life into tidy, comprehensible themes.

These books are all of an era (2005-2015), and there are probably newer ones. That said, they are a great guide for non biologists into how experts think things work.

[dkural]

This is a great list. I'll add the following covering related areas:

Cancer - by Weinberg

Introduction to Proteins - Kessel, Ben-Tal (an older classic is Proteins by Creighton)

Developmental Biology - Gilbert

Organic Chemistry - Clayden et al

[janeway]

We just called Janeway “the bible” for short.

Edit: I just realised what my username is here.

[_qua]

West's Respiratory Physiology if a beautiful example of stripping everything down to it's simplest possible level but no simpler.

[cannaceo]

Robbin's was great. Read it cover to cover many times in medical school.

[atemerev]

The Immune System by Peter Parham. A masterpiece.

[type0]

Williams Textbook of Endocrinology is a real gem as well

[progbits]

Concrete Mathematics [1], by Graham, Knuth and Patashnik. Wonderfully written (worth buying for the margin jokes alone) and approachable, but dense with information. Great overview of discrete math and algorithm analysis.

generatingfunctionology [2] by Wilf is an excellent companion book to Concrete Mathematics, going deeper into generating functions.

[1] https://en.wikipedia.org/wiki/Concrete_Mathematics

[2] https://www2.math.upenn.edu/~wilf/DownldGF.html

[ipnon]

The only math text that has made me laugh out loud, it’s really that funny. You get more of a feeling of sitting down with the authors in office hours than being emailed a list of theorems for homework. The effect is wonderfully motivating.

[sn9]

CM also includes solutions to all the exercises so it's great for self-study.

[kilotaras]

Designing Data Intensive Applications is one of the most useful books if you work with big systems.

Doubly so if you're actually working on a system like that.

Nicely threads a line between too dense and too watery.

[sarchertech]

One of the best books I’ve read in years. There’s very little fluff, which is exceedingly rare in a technical book.

[yodsanklai]

Yes, it's very often recommended. It's surprisingly entertaining for a technical book.

[ellen364]

Few of these books are “great works” in their field, but all changed my understanding of their topic.

- How to Read a Book by Adler and Van Doren. I was in academia when I read this and it had a huge impact on how I read and thought about academic papers.

- Intuitive Biostatistics by Motulsky. First stats book that I enjoyed. Emphasises the practice of statistics, particularly the assumptions and mistakes people tend to make.

- World War II Map by Map, published by DK. Had never previously been interested in WW2 history, but something about this took my interest. While reading it, I finally appreciated the scale and complexity of WW2.

- Bobby Fischer Teaches Chess. Working through this one meant I actually started getting better at chess!

- Common Sense Guide to Data Structures and Algorithms by Wengrow. The book that helped me become interested in data structures and algorithms, rather than being something I “should” learn about.

[mtlmtlmtlmtl]

>Bobby Fischer Teaches Chess Ah, memories. Got this book as a kid soon after I started playing at 11-12. It's just a nice puzzle collection, progresses really nicely in complexity. No notation needed, so very kid friendly. The mating pattern with sacrificing a queen on f7 and forcing the king into the corner with the bishop to deliver backrank mate was my first realisation of the beauty and art of chess, and made a real impression on me. It's quite contrived though, so I've yet to get it over the board. But ever since I read it I look for it whenever it seems even remotely possible. Highly recommended for parents of young kids who have just started learning.

Here's some other chess recommendations:

Silman's 2 books on positional play and endgames: these are fantastic books. The chapters are broken up by rating, ranging from beginner level to master strength(2000 ELO).

Other than those two, puzzle collections are always helpful. And for intermediates, game collections from string players. My favourite is Tal - Botvinnik 1962, written by Tal himself. Tal in my opinion is the greatest genius chess has ever seen(held back by his terrible health), and he was a fantastic author as well. Other great collections include Kasparov's My Great Predecessors and Fischer's My 60 memorable games.

Skip opening books entirely. Pick an opening and find grandmasters who play it. Study their games, understand the ideas of the opening. Memorising theory isn't really helpful below expert level(1800 ELO).

Thanks to OP for the trip down memory lane!

[ellen364]

Somehow forgot the two books that had the biggest influence on me. (And forgot for so long that I can’t edit the post.)

- The Population History of England, 1541-1871, by Wrigley and Schofield.

- English Population History from Family Reconstitution, 1580–1837, by Wrigley et al.

These books describe and analyse what was, for the time, an extraordinary amount of painstakingly pieced together historical data. Reading them changed my understanding of how history could be studied.

Each book is 700-800 pages, so a big commitment for anyone outside the field. But if anyone’s curious, Prof. Wrigley’s obituary has an excellent summary: https://www.theguardian.com/books/2022/mar/28/sir-tony-wrigl...

[Qem]

For the sciences that depend on higher maths, a Calculus book worth mention is "Elementary Calculus: An Infinitesimal Approach", by Jerome Keisler. One thing that makes learning Calculus harder than necessary is the clumsy epsilon and delta formalism, that became sort of the COBOL of Calculus teaching. This formalism is not the intuitive approach Newton and Leibniz used to develop Calculus, based on infinitesimals, that was shunned later because it took time until Abraham Robinson made it rigorous in the 1960s. The book by Keisler showcases nicely a way to improve higher math education, if academia had less inertia. The author made the entire book available for free online: https://people.math.wisc.edu/~keisler/calc.html See also: https://en.wikipedia.org/wiki/Nonstandard_analysis

[meiji163]

Some favorite math books

Intro to Smooth Manifolds, Lee -- sweeping intro to geometry with minimal prereqs, great at balancing the nitty gritty details with conveying intuition

A Course In Arithmetic, Serre -- classically terse and elegant intro to algebraic and analytic number theory. Goes from quadratic forms to Dirichlet's theorem to modular forms in a mere 100 pgs!

Princeton Lectures in Analysis, Stein & Shakarchi -- 4 books covering much of classical/modern analysis, they really shine in their discussion of applications

The large scale structure of space-time, Hawking & Ellis -- The most mathematically satisfying treatment of general relativity I've found. High points include proof of singularity theorems!

Spin Geometry, Lawson & Michelson -- Deep dive into the enigmatic "spin groups" and their applications in geometry. Also the only good (book) reference I could find on the index theorem

[bmitc]

Lee is a good book but Loring Tu's An Introduction to Manifolds is a masterpiece in clarity, conciseness, and notation. I'd heavily recommend it over Lee, which can be a bit meandering, for a first course, with a follow-up with Lee and others for material Tu leaves out. Tu's followups in differential geometry and algebraic topology also follow smoothly from it.

[madsbuch]

Types and programming languages, Benjamin Pierce: https://www.cis.upenn.edu/~bcpierce/tapl/

Its contents is what I consider the meta game of programming. Understanding types seems to be a real boost to think about architecture, implementation, etc.

[mananaysiempre]

It’s also surprisingly approachable, unlike most serious mathematical-logic(-adjacent) books. The three-page elementary treatment of the Knaster–Tarski fixed point theorem is worth reading even if you’re interested in cases for which it’s not sufficient (seriously infinite or order-theoretic things).

[civilized]

I'm tripping on the first sentence of the blurb:

> A type system is a syntactic method for enforcing levels of abstraction in programs.

Why is it called a syntactic method? Because type errors are caught at compile time, by analyzing the source code?

[curious16]

Have you read Robert Harper's Practical Foundations of Programming Languages?

[ly3xqhl8g9]

Artificial Intelligence: 1787, Immanuel Kant, Kritik der reinen Vernunft (Critique of Pure Reason)—where else to find purer reason than in a machine; unfortunately, Kant has written in Kantian using German words, fortunately, there is a recent, great Kantian to English translation in the works of 2020, Richard Evans, Kant's Cognitive Architecture, PhD Thesis [1]

Beingness: 1954, Martin Heidegger, Was heißt Denken? (What is Called Thinking?)—perhaps the machine can become intelligent following Kant, but if it is to become wise, it will follow Heidegger.

Self-reflection: 1985, Alexandre Grothendieck, Récoltes et Semailles, Réflexions et témoignage sur un passé de mathématicien (Reflections and Testimony on a Mathematician's Past)—insight into one of the most powerful, clear, and precise minds to have ever lived.

Socioeconomics: 1879, Henry George, Progress and Poverty: An Inquiry into the Cause of Industrial Depressions and of Increase of Want with Increase of Wealth: The Remedy—if the human civilization has any chance to exist and thrive beyond the 4th millenium, it's hard to imagine the implementation of that society being very far in principles from this initial specification.

[1] https://www.doc.ic.ac.uk/~re14/Evans-R-2020-PhD-Thesis.pdf

[_qua]

The Selfish Gene should be read by everyone who studies biology or life science. Modern biological sciences are underlied by an understanding of evolution an genetics. I had heard variants of the phrase "change in allele frequency in a population over time," as a description of evolution many times starting in high school. But it wasn't until I read The Selfish Gene in college that I really understood what this meant and how it should shape our view of biology.

[yboris]

I think a fantastic follow-up to The Selfish Gene is Daniel Dennett's From Bacteria to Bach and Back: The Evolution of Minds:

https://www.amazon.com/Bacteria-Bach-Back-Evolution-Minds/dp...

The author (a philosopher informed by scientific theories, writing on the subject for many decades) weaves together the grand story explaining biological evolution, evolution of minds, evolution of culture, and more (explaining how memes are a very useful concept to understand the tremendous non-biological changes over the course of the history of life).

[cercatrova]

Indeed. We are only vessels for our genes, what we do doesn't really matter as long as we pass our genes along, from the perspective of our genes.

I would also recommend other Dawkins books such as The God Delusion, it was one of the pivotal books that turned me from someone vaguely religious to an atheist. It explains simply how the various fallacies of religions are explainable and unwrappable.

[CSMastermind]

I would add that I think Dawkin's best work is The Ancestor's Tale.

Even if you have no interest in biology that book is still worth a read.

[irchans]

"Best Approximation in Inner Product Spaces" by Frank Deutsch.

This book is about the following problem,

"Given a point P and a set S in a vector space, find the point in S closest to P."

(The most common example of a vector space is the Cartesian Coordinate Plane which is also called R^2 because every point is of the form (x,y) where x and y are real numbers.)

This book is very simply written. All the details of the proofs are provided. Also, Professor Deutsch covers the history of many of the theorems in the book. Applications to Linear Regression, Interpolation, and Control Systems are given. The main prerequisite for reading the book is a course in mathematical analysis (Rudin or Royden) and a course in matrices or linear algebra. The book is based on the graduate level Approximation Theory course which Dr. Deutsch taught for several years.

[idlewords]

If you're interested in the effects social media has on political and civic life, these are two great books to read. One is recent, the other is a foundational classic of social psychology:

- Zeynep Tufekci, Twitter and Tear Gas, The Power and Fragility of Networked Protest (2017).

- Erwin Goffman, The Presentation of Self in Everyday Life (1956)

Goffman uses a theatrical metaphor to talk about how our behavior and social life is affected by our perceptions of who the audience is for our actions. Zeynep writes about how the magnifying and flattening effects of social media have been both a help and hindrance to large-scale organizing. Both are wonderful books.

[GekkePrutser]

"Unix for Programmers and Users" by Graham Glass and King Ables. Really great book that took you through the basics of Unix, the various shells, all the way to programming with system calls, sockets etc. Even dove into filesystem design, inodes etc. All in one reasonably compact book. I love books that can explain complex stuff in few words and do it well. I got it as part of my studies and I had worked through it already by the time I got the class :)

Later he made a special edition for this newfangled "Linux" stuff :) But the one I had was for the original Unix. Linux was already around at that time but still very much beta quality. At college we mainly used HP-UX and Sequent.

[Stamp01]

Seven Languages in Seven Weeks: A Pragmatic Guide to Learning Programming Languages by Bruce Tate

Seriously, check out this book. It's delightful! It'll level you up as a software developer. Also, I've heard it heavily influenced José Valim to create Elixir.

[macintux]

It changed my life: I discovered Erlang, which finally got me into FP, and took me to Basho where I got a big leg up on distributed systems and databases.

[irchans]

The older editions of "Physics for Students of Science and Engineering" by Halliday and Resnick are great.

Over the last 60 years, this has been the most commonly used physics text book in college. It's rather well written, and there are many very good homework problems. It covers the basics of mechanics and Electromagnetism and a few other topics also. The older editions have harder problems that are more instructive. By doing the homework problems, the reader learns physics, calculus, and the ability to manipulate and derive formulas.

[probablypower]

For power system operations: "Power System Stability and Control" by Prabha Kundur (https://www.amazon.com/System-Stability-Control-Prabha-Kundu...)

It is the bible of modern power system operations, and it will become more and more important as more renewable energy comes online. Understanding the concepts presented in this book is the difference between "why haven't we hit 100% renewables yet?!" and "we need market incentives for inertial ancillary services".

[thro388]

》as more renewable energy comes online.

Maybe better name is "unstable" energy. Some types of renewables are stable (water dams, geothermal).

[boruto]

Would you recommend it to a non electrical engineer. Who is interested in power systems?

[532nm]

"The Art of Insight in Science and Engineering: Mastering Complexity" by Sanjoy Mahajan.

It beautifully treats estimation and problem solving techniques, illustrated by examples from science and engineering. Instead of aiming for a complete, thorough and accurate treatment of problems, its goal is to teach shortcuts to sacrifice some accuracy for much reduced effort. This is a refreshing change to academia where rigor is often pursued at all cost. But in the real world rigor rarely matter, and simplifications are almost always worthwhile, especially initially since we can always refine models if required.

I first read it as an undergraduate and use the estimation and problem solving techniques from it almost daily. Though well hidden, the pdf is available for free on the website of the publisher.

[themantri]

I got hold of this book after reading your comment and it's already one of my favourite books.

[danielheath]

("Data and Reality")[https://www.goodreads.com/book/show/1753248.Data_and_Reality] - despite its age (written before SQL was mainstream) it remains a short, accessible read that lays out how to think about modeling an information schema, particularly where the same piece of information may be used in separate parts of the organisation.

[rrampage]

If reading Data and Reality, please read the 2nd edition [1] (the 3rd edition has a co-author who replaced half the stuff with his own "notes"). The 2nd edition is out of print but you can get a PDF here [2]

[1] https://buttondown.email/hillelwayne/archive/why-you-should-... [2] https://github.com/jhulick/bookstuff/blob/master/Data%20and%...