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Mastering Deep Learning: A Complete Introduction for Beginners and Newbies
If you are looking for a complete introduction to deep learning, this book is for you.
If you have just heard about deep learning and data science, this book is the right place to start. And if you are amazed by cool projects built by others and you want to build one of those yourself, this book is definitely for you. Not only that, if you're going to start an exciting new career which can provide you with both financial and intellectual satisfaction, this book will assist you to reach that goal.
Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. Readers are advised to adopt a hands on approach, which would lead to better mental representations.
Does this book include everything I need to become a deep learning expert?
Unfortunately, no. This book is designed for readers taking their first steps in machine learning and deep learning further learning will be required beyond this book to master all aspects.
Can I have a refund if this book doesn’t fit for me?
Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform.
If you have just heard about deep learning and data science, this book is the right place to start. And if you are amazed by cool projects built by others and you want to build one of those yourself, this book is definitely for you. Not only that, if you're going to start an exciting new career which can provide you with both financial and intellectual satisfaction, this book will assist you to reach that goal.
Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. Readers are advised to adopt a hands on approach, which would lead to better mental representations.
Does this book include everything I need to become a deep learning expert?
Unfortunately, no. This book is designed for readers taking their first steps in machine learning and deep learning further learning will be required beyond this book to master all aspects.
Can I have a refund if this book doesn’t fit for me?
Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform.
121 pages, Kindle Edition
Published January 16, 2019
11 people are currently reading
4 people want to read
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Displaying 1 - 2 of 2 reviews
February 8, 2019
Very short and shallow. Full of errors and typos.
April 24, 2019
Deep Learning seeks to mimic how humans learn (i.e., the brain processes of how humans learn in their cerebral cortex) and apply this mimicry to how computer programs are written. Thus, we have terms like a "neural network" which does not refer to a brain (made up of neurons) but to a web of computer cells which "learn" how to produce certain output from input data.
One interesting application of such is detailed in the book. A Generator attempts to produce a fake image, and a Discriminator attempts to figure out which items are fakes. When paired together with machine learning, they can produce a fairly good fake image.
What's somewhat scary about this technology is seen in the newspapers and social networks of today. "Fake news" is not merely news which is contrary to a certain viewpoint; fake news can be a video clip of some famous person saying some phrase that she never uttered! If that doesn't sound like 1984 (or 2016?), I don't know what does.
One interesting application of such is detailed in the book. A Generator attempts to produce a fake image, and a Discriminator attempts to figure out which items are fakes. When paired together with machine learning, they can produce a fairly good fake image.
What's somewhat scary about this technology is seen in the newspapers and social networks of today. "Fake news" is not merely news which is contrary to a certain viewpoint; fake news can be a video clip of some famous person saying some phrase that she never uttered! If that doesn't sound like 1984 (or 2016?), I don't know what does.
Displaying 1 - 2 of 2 reviews