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

A classic reading on the field of programming language theory is the Sebesta one: Concepts of Programming Languages.

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.

I'm not sure batteries are the answer on a grid scale. From the grid/market perspective, they're incredibly expensive energy time machines. They also come with their own environmental issues. Batteries make sense if you need to make small islanded systems, or need black start capabilities. If you just want to teleport energy/inertia around I think the answer is old school flywheels, pumped hydro, and synchronous condensers.

The real lowest hanging fruit is industrial demand-side response. I'm actively working on this from the grid side, implementing partial control room scada control of heavy industry for real-time grid balancing. Costs a few engineers some grey hairs, which is a lot cheaper than building grid scale batteries to provide the same end result.

How Brands Grow by Byron Sharp is the most compelling overview I have come across about how marketing works at the aggregate level. Despite its flaws, Thinking Fast and Slow is a good companion piece inasmuch as it sheds light on how decisions are made at the individual level.

"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.