QuickStart Guide to (Ultra-)High Performance Visualizations

Disappointing. The description oversold what is actually inside.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. The chapters on data visualization are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. The writing is direct and does not waste space on filler, which I value in a technical book. A few of the examples could be more realistic, but the underlying points come across clearly. Two stars. The subject deserves a better treatment than this.

Strong content, uneven pacing. I would still recommend it.

I had been on the fence about this one for a while, and I should have bought it sooner. The explanations are careful without being condescending, which is a difficult balance to strike. A couple of chapters felt like they could have been merged, but that is a minor complaint. A few of the examples could be more realistic, but the underlying points come across clearly. A good addition to a technical library, as long as you know what you are buying.

Good book. The writing is direct and the author is honest about limits.

I had been on the fence about this one for a while, and I should have bought it sooner. I found myself making notes in the margins, which is always a good sign. The book rewards careful reading. Skimming it would be a mistake. A good addition to a technical library, as long as you know what you are buying.