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Deep Learning: An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence
If you want to learn about Deep Learning then keep reading...
It’s said that filling the observable universe with an infinite number of monkeys on infinite typewriters and letting them type for an infinite amount of time would eventually produce Shakespeare’s works. However, what would happen if we applied the infinite monkey theorem to computer programs capable of learning and evolution? Would a thousand such smart machines thrown together and allowed to evolve undisturbed produce a human mind or something much greater? Well, scientists decided to give it a go and see what happened.
That line of reasoning, alongside the fact we’ve nearly exhausted all the possible progress of the scientific method, motivated the creation of deep learning, a process in which computer programs meant to learn and adapt to the environment evolve on their own without any human intervention or even knowledge how their evolution occurs. Such software could eventually develop a will of its own and escape containment or even be intentionally unleashed on the planet as a cyber-weapon.
This book analyzes the validity of such seemingly preposterous possibilities while compiling and investigating academic research concerning deep learning and its practical applications, referencing, and quick summarizing of numerous academic writings that need to be meticulously picked apart by the curious reader – who can then truly understand what lies ahead of us all in a future dominated by smart machines. If that same reader finds themselves starting up exhaustive conversations with complete strangers on deep learning, this book has done its job superbly.
Deep An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence cover topics such
So if you want to learn about Deep Learning without having to go through heavy textbooks, click "add to cart"!
It’s said that filling the observable universe with an infinite number of monkeys on infinite typewriters and letting them type for an infinite amount of time would eventually produce Shakespeare’s works. However, what would happen if we applied the infinite monkey theorem to computer programs capable of learning and evolution? Would a thousand such smart machines thrown together and allowed to evolve undisturbed produce a human mind or something much greater? Well, scientists decided to give it a go and see what happened.
That line of reasoning, alongside the fact we’ve nearly exhausted all the possible progress of the scientific method, motivated the creation of deep learning, a process in which computer programs meant to learn and adapt to the environment evolve on their own without any human intervention or even knowledge how their evolution occurs. Such software could eventually develop a will of its own and escape containment or even be intentionally unleashed on the planet as a cyber-weapon.
This book analyzes the validity of such seemingly preposterous possibilities while compiling and investigating academic research concerning deep learning and its practical applications, referencing, and quick summarizing of numerous academic writings that need to be meticulously picked apart by the curious reader – who can then truly understand what lies ahead of us all in a future dominated by smart machines. If that same reader finds themselves starting up exhaustive conversations with complete strangers on deep learning, this book has done its job superbly.
Deep An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence cover topics such
So if you want to learn about Deep Learning without having to go through heavy textbooks, click "add to cart"!
100 pages, Paperback
Published October 3, 2018
21 people are currently reading
7 people want to read
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January 28, 2019
The book has a lot of good details on data science and deep learning. The author is very knowledgable on the subject and has gathered details on many use cases. I think as a collection of use cases it is a great book. My reason for only giving 2 stars is that I believe it is not thorough enough in explaining some of the cases and the conclusions the author presents are sometimes not valid in my opinion. In general this an excellent for someone who is interested in a great collection of deep learning use cases. I believe the conclusions provided for some cases need a more thorough analyses.
Displaying 1 of 1 review