Thomas

by far the best book on stoicism I have found

Revisado: 05-04-24

this is by far the best book on Stoicism I found. Even though it is at the surface about one particular philosopher, it is really a great summary of the stoic philosophy itself.

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a classic.very entertaining way of teaching

Revisado: 04-28-19

a classic. old but still relevant. makes the material fun. I stumbled upon it because one of the best books on devops is inspired by it, it's called The Phoenix project. that one is even more highly recommended.

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Great for an audiobook

Revisado: 02-01-19

Obviously the material is very hard to present in an audiobook, but this does an excellent job. I usually do have my laptop open with the supplementary material, but it still worth getting the audiobook because I can do chores, etc and only glance at the screen occasionally. Highly recommended!

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esto le resultó útil a 7 personas

Single best book about the topic

Revisado: 02-01-19

I also like ramit sethi's drea job course, which is much more in-depth. This book has a different approach and focuses more on leveraging recruiters rather than networking, which in a way easier. Also, it's a fraction of the price, though I would suggest investing in both...

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as good as an audiobook about this topic gets

Revisado: 02-01-19

worth it if you dont have time to read an actual book or watch a lecture. if you do have the time, check out Stanford's free courses (first one is called DB1).

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esto le resultó útil a 1 persona

not suitable for audiobook

Revisado: 01-26-19

I was already skeptical if it would be suitable for an audiobook, but given the many good reviews I gave it a try, even though I wasn't sure if the reviews sounded entirely genuine. they clearly are not - audible, please get rid of the fake reviews. I'm returning it.

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great material but could be organized better

Revisado: 08-18-18

my main complaint is that the book is not organized into chapters. this often made it hard to go back to listen to a specific part again.

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It's hard to explain machine learning without math

Revisado: 02-19-18

Would you recommend this book to a friend? Why or why not?

I don't really fault the author, but it is very hard to explain such a complicated subject as machine learning in a simple way. Indeed, if I hadn't read Domingues' "the master algorithm" – which I highly recommend instead – I would say it's impossible. Even if you only want to know what all the hype is about without being interested in all the details, I'm not sure this book will be worth your time.

It's hard to find books on machine learning that don't use advanced math. Unfortunately, I think that, in order to go beyond the surface, some amount of math is necessary – even for in introduction. Some things are actually more clear if you put them in equations. Thus, what I would recommend instead (in addition to reading "the master algorithm" for the intuition), is to watch Domingues' (search for "csep 546") and Victor Lavrenko's lectures on machine learning on YouTube, as well as reading Hastie & T.'s "introduction to statistical learning" (which also has free videos available somewhere).

If this is not an option for you because you're looking for a easy read or something available as an audiobook, I can recommend Nate Silver's "the signal and the noise", as well as books that focus more on applications of machine learning, as well as its effect on the economy and society, etc. (my personal favorites are "the second machine age", "machine, platform, crowd", and "the platform revolution" – all available as audiobooks).

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esto le resultó útil a 3 personas

Not very deep

Revisado: 02-15-18

What could have made this a 4 or 5-star listening experience for you?

More focus on background. I was hoping to get a better understanding of life in Appalachia, but didn't learn much beyond the little I already knew. Granted, if you are not interested in learning anything generalizable, but read the book merely for entertainment, the book is fine.

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Author lacks foundational understanding of statistics

Revisado: 02-15-18

What could have made this a 4 or 5-star listening experience for you?

Okay overview of the application of big data analytics in the business world. My main complaint is that in several places of the book it becomes clear that the author lacks an understanding of the most basic foundations of statistics, as well as the cognitive psychology of decision-making.

For example, when he discusses the downsides of applying big data analytics, he notes that due to the inherent uncertainty of the world, our point predictions will sometimes be wrong (e.g., not everyone who are algorithms singles out as being a risky borrower will actually default). There are two mistakes in this reasoning: Most importantly, one of the main goals of statistics is to QUANTIFY UNCERTAINTY. Thus, no reasonable model would predict that something is going to happen with 100% certainty (like in his examples). Only someone not schooled in statistical thinking would ignore those estimates of uncertainty and simply focus on the point estimate.
Secondly, we have to take into account how humans would decide in the absence of quantitative models. It turns out that the human brain is very bad at thinking probabilistically, and usually thinks in terms of categories and representative examples of these categories. As a result, it is prone to to stereotypes, neglecting the variation within these categories. Thus, the question is not whether statistical models lead us to neglect uncertainty, but whether they neglect uncertainty LESS than human decision-makers would in the absence of quantitative models. (A much better treatment of the risks of big data analytics is found in "Machine, Platform, Crowd", which I can highly recommend.)

Overall, these flaws in the author's thinking makes me question his competence on the subject. Machine learning methods have made statistical models much more powerful, so it is more dangerous than ever if these models get applied without a full understanding of them.

Would you ever listen to anything by Bernard Marr again?

No

What about Piers Wehner’s performance did you like?

It was good

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