The Master Algorithm
How the Quest for the Ultimate Learning Machine Will Remake Our World
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The Master Algorithm
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Narrateur(s):
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Mel Foster
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Auteur(s):
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Pedro Domingos
À propos de cet audio
Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars. These programs are already helping us fight the war on cancer and predict the movements of the stock market, and they are making great headway with instant language translation and discovering new laws of nature.
But machine learning is incomplete, and its practitioners across the globe are seeking the most powerful algorithm of all. The Master Algorithm will not be limited to solving particular problems but will be able to learn anything and solve any problem, however difficult, and Pedro Domingos, a trailblazing computer scientist, is at the very forefront of the search for it. With the Master Algorithm in hand and data as its fuel, machine learning - essentially the automation of discovery, a kind of scientific method on steroids - will become the most powerful technology humanity has ever devised. And The Master Algorithm will be its bible.
©2015 Pedro Domingos (P)2015 Brilliance Audio, Inc.Ce que les auditeurs disent de The Master Algorithm
Moyenne des évaluations de clientsÉvaluations – Cliquez sur les onglets pour changer la source des évaluations.
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Au global3 out of 5 stars
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Performance4 out of 5 stars
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Histoire2 out of 5 stars
- Darrell F
- 2019-02-22
A long-winded textbook approach
There are definitely some great practical examples of various algorithms and real-world practices, but I had to speed up playback to get through it. The typical textbook style vernacular to appear learnid and lengthen content (imagining the author sitting thinking he's paid by the word, thesaurus in hand).
Lastly, the final chapter, and how the author perceives A.I. is either extremely arrogant or surprising ignorent.
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Au global3 out of 5 stars
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Performance2 out of 5 stars
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Histoire2 out of 5 stars
- Jay Han
- 2018-09-13
pretty well written but still vague idea
I'm reading it for the second time and still don't understand what the Master Algorithm looks like in any tangible manner. it seems to be a vague idea.. Mostly, okay materials but not a great book for those who want to get any new insights into AI and Machine learning or those who want to learn basic of ML.. I would take this book as a ML/AI fantasy novel #Audible1
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Au global5 out of 5 stars
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Performance5 out of 5 stars
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Histoire5 out of 5 stars
- Rick Zhong
- 2018-03-24
Can't wait for a new revision of this great book!
Enjoy listening many aspects of ML from your perspectives, even it is almost 3 years old, now it is 2018, I found it is still relevant to current development of ML. Can't wait for a new revision of this wonderful book! Thank you! -Rick
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Au global4 out of 5 stars
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Performance4 out of 5 stars
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Histoire3 out of 5 stars
- Bogdan
- 2019-05-24
Worth the read for beginners
The book covered many different topics within computer algorithms and machine learning, as well as examples for their uses, but was not extremely specific on their inner workings. Good read for those with minimal prior machine learning understanding or experience. Also used a lot of analogies, some of which did not have clear correlation to the idea.
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1 personne a trouvé cela utile
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Au global3 out of 5 stars
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Performance2 out of 5 stars
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Histoire2 out of 5 stars
- Etienne Dumouchel
- 2022-08-11
Downplays need for vigilance. Too optimistic.
I think something like a master algorithm will have positives, but my issue is mainly that any problem that currently exists risks becoming more sophisticated as a result of such an algorithm.
Algorithms might face issues that are similar to the disasters created by infrastructure that isn't maintained.
Also, if you can't examine the black box where an algorithm makes decisions, how can you be certain the algorithm is functioning as intended?
I also think people are really good at shifting responsibility away from themselves when something bad happens. I mention this because Pedro says that if an algorithm kills someone, they'll be arrested. No legal process is that easy or clean. I think there's no guarantee that someone who makes a bad system will not go on to make more.
Lastly, if the master algorithm is not open sourced, most of us will suffer.
Oh I forgot. The book feels condescending.
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