I realize this is a bit off topic, but no, the parent poster should not. It's a mish-mash of poorly explained introductory probability material. There are numerous other textbooks on statistical aspects of heavy-tailed random variables that would be far more insightful.

I enjoyed it, but I can see why someone might get that impression. Care to share other reads?

Didier Sornette, Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder. Springer, 2nd edition.

This covers the mathematics of heavy-tailed distributions and a lot of fun applications, and also touches on some other interesting, Taleb-esque topics (fractals, renormalization group).

For financial stuff in this vein (heavy tails), Bouchaud has some books with various coauthors (e.g. Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management). Admittedly I have only browsed them, but what little I've read has been good.

Also, on a tangent which may interest you, Charles Martin and Mike Mahoney (of UC Berkeley) have some recent work which uncovers heavy-tailed laws in neural networks. You can get started here and follow the citations: https://arxiv.org/abs/1901.08278.

Taleb is a great writer, but not a great teacher.