Factfulness
Ten Reasons We're Wrong About The World - And Why Things Are Better Than You Think
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4.3 • 13 Ratings
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- 79,00 kr
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- 79,00 kr
Publisher Description
'One of the most important books I've ever read - an indispensable guide to thinking clearly about the world' BILL GATES
'A hopeful book about the potential for human progress when we work off facts rather than our inherent biases' BARACK OBAMA
The international bestseller, inspiring and revelatory, filled with lively anecdotes and moving stories, Factfulness is an urgent and essential book that will change the way you see the world, and make you realise things are better than you thought.
*#1 Sunday Times bestseller * New York Times bestseller * Observer 'best brainy book of the decade' * Irish Times bestseller * audiobook bestseller * Guardian bestseller *
APPLE BOOKS REVIEW
Poverty is down, life expectancy is up and—surprise!—the world is a much brighter place than we think. That’s the core tenet of Factfulness, a masterful recalibration of global misconceptions from breakout TED speaker Hans Rosling, a medical doctor and renowned international health professor. Using clear-eyed reasoning, anecdotal support and “data as therapy”, Rosling shows how we’ve let fear, overgeneralisations, and impatience blind us to major leaps in human progress. Factfulness is a crucial lesson for confusing times, reminding us that the path ahead lies not in panic but in clear thinking.
Customer Reviews
Good, relevant content, but hard to understand
This book goes through the mathematical foundations for deep learning, and focuses on linear regression using matrices as an entry point. With this book, you can get a good understanding of how neural nets work. The information is hard to get, so you need to be prepared to put in a significant effort. It only covers the foundations, so you likely need more reading material for applications of neural nets.
Some of the author’s choices make it time-consuming to comprehend. The author apologizes for many of these issues in the book, rather than fixing them.
1. The book seems to have been converted from a Kindle format, and this makes both maths formulas and Python code hard to read.
2. The use of symbols is inconsistent. Sometimes a new symbol is used instead of an old. Some symbols are not explained when first used. E.g. the “w” matrix is introduced without explaining that it's the weights. Soon after, “w” is used for a general statistical variable. A few lines further down, mu is used for what seems to be the same general statistical variable, without any explanation of the change.
Some places the transposed weights are multiplied with the sample positions. Other places the sample positions are multiplied with the weights.
3. The maths explanation is not going through all the details. The author assumes the reader to know the all relevant maths, and largely presents solutions while encouraging the reader to do the maths himself to prove that he’s right. It’s doable, but for me it meant looking up lots of maths rules that I had not used in years. Maths formulas in the book don’t distinguish well between matrix cross product and dot product.
All in all, I don’t regret getting the book, but I wish it was easier to digest. The author could have done a lot more to help comprehension