Free Download The Deep Learning Revolution
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The Deep Learning Revolution
Free Download The Deep Learning Revolution
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Product details
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Audible Audiobook
Listening Length: 8 hours and 5 minutes
Program Type: Audiobook
Version: Unabridged
Publisher: Tantor Audio
Audible.com Release Date: January 29, 2019
Language: English, English
ASIN: B07MM8F42R
Amazon Best Sellers Rank:
This book is NOT about deep learning principles or practice. Despite its titillating title, this is strictly a personal memoir which deals entirely in stories about past colleagues, students, and friends who worked with the author in developing rhe field of neural networks.Since about 1980 Professor Terrence Sejnowski has worked with biologically inspired neural nets. However, his work is NOT notable for the theory behind or the development of today's deep learning algorithms that arose circa 2006. Thus this book consists wholly of a light historical introduction to most of the people who were active in the days of early NNs (since 1975), and Dr Sejnowski's kinship with them, but little beyond that.The text explains none of the technical details of Dr Sejnowski's work, nor the work of other NN pioneers, nor does it offer any tangible predictions or insights into the likely implications of NNs, deep learning, or AI.Frankly, titled as it is, this book was a HUGE disappointment to me. It doesn't delve into deep learning nor any other facet of artificial intelligence to any extent. Read it only if you want a breezy history of Dr. Sejnowski.
This book is a memoir. In addition, although the author does not explain or go into detail about about deep learning, he gives a good perspective on its development over the time of his career, and places it in a larger perspective. Despite not explaining or clarifying technical terms, theory and practical methods, his book is fairly enlightening, as he contributed in important ways to the field, and knew or worked with numerous researchers who contributed significantly. The book has numerous insightful remarks. He seems to have a very open mind, an enormous amount of curiosity, and a tremendous dedication. I recommend his book to achieve some perspective on this currently important field, which has much potential for contributing to many fields of study, and itself has been a multidisciplinary field. Deep learning seems to have acquired much more importance in recent years with the great progress that has been made in computers, in their computing power, miniaturization and success that deep learning has achieved in numerous specialized areas.
This is a great book for you to understand and appreciate the work of those scientists who contributed the success of today's machine learning approach to artificial intelligence.I am a practitioner of mathematical modeling with different methods. I always believed the nature can and did give us a lot inspiration for scientific discovery and the neural network borrowed the idea from biological neural structure. But this book demonstrated how extensively our progress in neurobiology and artificial intelligence directly derived from biological study of organic structure.Highly recommend this book for those who have a technical background to enjoy the anecdotes as "gossipy" in their spare time. For some topic you will enjoy more if you know the technical background.
Did not like the book and stopped reading half into it. The book is not for an average reader. Felt like you would need a PhD in neuroscience to understand it. Waste of money!
The Information Age will mature with AI. It is all not so simple as you might think. Sejnowski was a major shaper of this field and I’m not aware of anything better.I’m still waiting for the Tao of AI, etc.
Very interesting and insightful summary and history of artificial intelligence. I am also very impressed by the quality of the print book . The cover and pages are some of the best quality I have seen in a hardcover book.
Wonderful clear and concise explanation of AI and its development
Very interesting to read, the author describes the long path deep learning took until it became massively used and explains also the origin of some of the ideas in neuroscience.
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