Nassim Nicholas Taleb

‘A breakthrough book. Wonderfully applicable to everything in life, and funny as hell.’ Nassim Nicholas Taleb

I will write a longer review, but this is a monument, not just a book. And the beginning of a new cultural program.

On a scale of 0 to 100, paternity tests count as 99.99 and written/oral history should count for .01. Apply that to populations. That’s plain statistics/probability. We are seeing science in action: information theory displaces BS, the handwaving just so stories we got from historians.
(A longer review to come).

I know which books I value when I end up buying a second copy after losing the first one. This book gives a complete overview of the basis of probability theory with some grounding in measure theory, and presents the main proofs. It is remarkable because of its concision and completeness: visibly prof Varadhan lectured from these notes and kept improving on them until we got this gem. There is not a single sentence too many, yet nothing is missing.
For those who don't know who he is, Varadhan stands as one of the greatest probabilists of all time. Learning probability from him is like learning from Aristotle.
Varadhan has two other similar volumes one covering stochastic processes the other into the theory of large deviations (though older than this current text). The book on Stochastic Processes should be paired with this one.

As a practitioner of probability, I've had to read many books on the subject. Most are linear combinations of other books and ideas rehashed without real understanding that the idea of probability harks back to the Greek pisteuo (credibility) [and pithanon that led to probabile in latin] and pervaded classical thought. Almost all of these writers made the mistake to think that the ancients were not into probability. And most books such as "Against the Gods" are not even wrong about the notion of probability: odds on coin flips are a mere footnote. Same with current experiments with psychology of probability. If the ancients were not into computable probabilities, it was not because of theology, but because they were not into highly standardized games. They dealt with complex decisions, not merely simplified and purified probability. And they were very sophisticated at it.

The author is both a mathematician and a philosopher, not a philosopher who took a calculus class hence has a shallow idea of combinatorics and feels dominated by the subject, something that plagues the subject of the philosophy of probability.

This book stands above, way above the rest: I've never seen a deeper exposition of the subject, as this text covers, in addition to the mathematical bases, the true philosophical origin of the notion of probability. Finally, Franklin covers matters related to ethics and contract law, such as the works of the medieval thinker Pierre de Jean Olivi, that very few people discuss today.

This book takes us through the formulation of the theorems in "On Landau damping" by Clément Mouhot and Cédric Villani. Villani is playful in real life, his research is playful, and the book is playful.

This is a gem for a singular reason. One sees exactly how Villani (or a pure mathematician) goes from abstract to abstract without ever exiting the world of pure and symbolic mathematics, even though the subject concerns a very concrete real-world topic. I kept waiting for him to use simulations or even plots to see how the equations worked. But he did not ... he and Mouhot had recourse to outside help (a student or an assistant) for the graphs and he camly noted that they "looked" great. Later in the book he relied on others to do the numerical work... as an afterthought. Most physicists, quants, and applied mathematicians would have played with a computer to get the intuition; Villani just worked with mathematical objects, abstract mathematical objects, and very abstract at that. And this is a big deal for the subject because it belongs to a certain class of problems that do not have analytic solutions, usually requiring numerical approaches.

Landau damping is about something many people are indirectly familiar with. Some history: Fokker–Planck equation, itself the Kolmogorov forward equation, is used commonly as the law of motion of particles (hence diffusions in finance). We quants use it in the main partial stochastic differential equation. In plasma physics it is related to the Boltzman equation, which, by using mean-interraction in place of every interration (mean-field), leads to the Vlasov equation. Landau damping is (sort of) about how things don't blow up because of some exponential decay. Proving it outside the linear version remained elusive. Villani and Mouhot set to prove it. They eventually do.
One note. I read it in the English translation (because I was in a hurry to get the book), but noticed an oddity that may confuse the reader. "Calcul" in French does not mean "calculation" (in the sense of numerical calculation) but "derivation", so the reader might be confused about calculations thinking they were numerical when Villani stayed at the abstract/symbolic level.

I would have read the book in one sitting. It grips you like a detective novel.

PS- Some UK BS operator, the type of journalist with an attempt at some PhD in something related to physics who thinks he knows it all and is the representative of the general public trashed the book in the Spectator. Ignore him: the fellow is clueless. Look at reviews by PRACTICING quants and mathematicians. I do not think there is another book like this one.

There is something admirable about the school of the Russians: they are thinkers doing math, with remarkable clarity, minimal formalism, and total absence of unnecessary pedantry one finds in more modern texts (in the post Bourbaki era). This is of course surprising as one would have expected the exact opposite from the products of the communist era. Mathematicians should be using this book as a model for their own composition. You can read it and reread it. Professors should assign this in addition to modern texts, as readers can get intutions, something alas absent from modern texts.

Very comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Very useful as a reference book (actually, there is no other complete reference book).

The authors are the real thing (Tibshirani is the one behind the LASSO regularization technique).

Uses some mathematical statistics without the burdens of measure theory and avoids the obvious but complicated proofs.

I own two copies of this edition, one for the office, one for my house, and the authors generously provide the PDF for travelers like me.

Here is what I wrote in my endorsement: Emanuel Derman has written my kind of a book, an elegant combination of memoir, confession, and essay on ethics, philosophy of science and professional practice. He convincingly establishes the difference between model and theory and shows why attempts to model financial markets can never be genuinely scientific. It vindicates those of us who hold that financial modeling is neither practical nor scientific. Exceedingly readable.
From the remarks here, people seem to be blaming Derman for not having written the type of books they usually read... They are blaming him for being original! This is very philistinic. This book is a personal essay; if you don't like it, don't read it, there is no need to blame the author for not delivering your regular science reporting. Why don't you go blame Montaigne for discussing his personal habits in the middle of a meditation on war inspired by Plutarch?

I feel guilty for not having posted a review earlier: I owe a lot to this book. I figured out the value of intensity training and maximizing recovery. I use the ideas but with minor modifications (my own personal workout is entirely based on free weights and barbells, but I incur --and accept --a risk of injury). I have been applying the ideas for more than three years. Just get over the inhibitions (and illusions of control) and accept the idea of training less.

If you want an introduction to information theory, and, in a way, probability theory from the real front door, this is it. A clearly written book, very intuititive, explains things, such as the Monty Hall problem in a few lines. I will make it a prerequite before more technical great books, such as Cover and Thompson.

I read this book after completing my exposition of overcompensation, how a stressor or a random event causes an increase in strength, in excess of what is needed, like a redundancy. I was also looking for evidence of convex reaction to stressor, or the effect of a mathematical property called Jensen's inequality in domains and found it exposed here (in other words, why a combination low dose (most of the time) and high dose (rarely) beats medium dose all the time. The authors presents the evidence for the phenomenon in the following: 1) acute stressors cum recovery beat both absence of stressors and chronic ones (this includes thermal variations); 2) stressors make one stronger (post traumatic growth); 3) risk management is mediated by the deep structures in us, not rational decision-making; 4) winning causes an increase in strength (the latter are more complicated effects of convexity/Jensen's Inequality).
Great book. I ignored the connection to financial markets while reading it. But I learned that when under stress, one should seek the familiar.
Bravo!

Bertaud knows cities inside out. It is a pleasure to read something by a person who knows his subject in so much depth. He reveals how planning can mess up cities, how the market is more intelligent than planners, etc.
Aside from the potent Hayekian argument, Bertaud gave me some intuition for future real estate investments: a city is a labor market since people change jobs and companies add and subtract employees. Any form of planning needs to accommodate such a fact. And if cities are principally labor markets, they should both concentrate and differentiate along with globalization.