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Publisher's Summary

The very schemata of Convolutional Neural Networks and the technology behind it was inspired by our biological human brains!

Its a known fact that computers can store exponential amounts of information on their hard-drives. But our human brains have a set capacity and just cannot compete against technology on this front. However, our biological brains can outpace a computer in some other everyday functions we take for granted.

Engineers and scientist are discovering ways to model our human brains and integrate certain aspects of it to create what we know as "neural networks". In essence, replicate the fine tuning, inner complexities and intricacies the human brain possess.

In my book, Convolutional Neural Networks Guide to Algorithms, Artificial Neurons, and Deep Learning, you will learn the following concepts:

  • Fundamentals of neural networks
  • Intelligent systems
  • Functioning of the feed-forward neural network
  • Back-propagation
  • Algorithms
  • And, much, much more!

You do not want to miss out on this incredible offer! Take this opportunity to learn about the next big innovation in technology and real-world applications of the next potential trillion-dollar industry (artificial intelligence) that will take the world by storm.

PLEASE NOTE: When you purchase this title, the accompanying reference material will be available in your Library section along with the audio.
©2018 Healthy Pragmatic Solutions Inc. (P)2018 Healthy Pragmatic Solutions Inc.

What members say

Average Customer Ratings

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Poorly written Wikipedia post book scam

This was horrible and I hope that no o e else ever spends $ on this scam. The "book" is little more than a grammar and pronunciation error ridden Wikipedia entry. Read Wikipedia or buy a real book on this topic.

3 of 3 people found this review helpful

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Complete intuitions

Complete intuitions and coding of the latest deep learning network architectures. This is absolutely one of the book's differentiation. Since I am picking up the field anew after some time of dusting neural networks, my rate of comprehension was slower at the start.

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You will understand about Neural Network

Practical, hands-on and with a generous set of samples covering even some rather recent topics. Gets the job done.

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Totally enjoyed and fruitful time investment

I feel it should definitely be supplemented on a book with more theory on neural networks, Excellent book. Enough detail to get moving, just short enough to fully digest.'

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Great and to the point

I highly recommend this book to technically-proficient deep learning enthusiasts. For those just starting out with deep learning or both, you will want to supplement this book with the more introductory material.

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A very useful resource!

Fun and easy follow to work through. Doesn't get extremely technical or go into great depth and covers a lot of material.

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Recommended!

There were amazing easy examples which were perfect for a starter. All in all, I would recommend this book to new learners and advanced learners as both can benefit.

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BETTER CHOICE

This Book is very detailed and walks you through the Neural Networks Guide to Algorithms very well. I am fairly new to Machine Learning and I think this is a good step for a guide.

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develop deep learning

Any additional comments?

As a Computer Programmer Analyst and a Computer Science graduate, I considered this book is a good and intelligent book in the field of computer science and androids theory.

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straight forward

What I liked best was his treatment of discrete systems. It makes digital filter design simple. This book was a nostalgic review for me. People in EE programs should buy it.

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  • Bill
  • 03-13-18

good job

Does a really good job of showing how the principles of ml are actually pretty accessible. Doesn't dumb down but explains it clearly and as the name promises, gently.

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  • bella
  • 03-13-18

very easy to understand

There are a few typos, but nothing that prevents the message from getting across. The author did a great job taking me step by step to create a neural network. Very easy to understand.

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  • Ashley H McNeely
  • 03-13-18

looking for

If all you're looking for is a brief intro to neural networks, than this is an awesome little book. The expansion's are good and the code samples are thorough and ready to follow. This is not an in depth study, but it is exactly what I was looking for.

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  • Andrea
  • 03-13-18

special guide

This book is special in many ways. It provides a gentle, yet rather thorough introduction to Neural Networks. It covers the Maths (mostly Matrix multiplication and some simple calculus for gradient descent) in a very concise, practical way that should be easy to follow for an audience with basic math training

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  • begum
  • 03-13-18

5 stars

I am a software developer going through many machine learning tutorials, but I discovered I didn't have a clue how they worked. I just put in code and watched it do random magic. That was until I listen this book. Now I feel like I have a decent grasp of the concepts and I will be revisiting those machine learning walk throughs.

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  • james
  • 03-13-18

deeper understanding

If you are new to programming of just want a solid understanding of neural networks, this is the book that makes it all clear. From step one, this easy to read and understand guide is a must listen. This is the one I refer other too. And, it is the one I keep on my desk while the others are on the shelf. It is the gateway to deeper understanding

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  • adam
  • 03-13-18

very good practical guide

Very good practical introduction to neural networks. My only gripe is the format of the book (which is essentially a PDF; no text reformatting, zooming, table of contents, etc) and that some of the examples are a little difficult to tell what's going on. That said, I worked through the book quite easily even with almost no background on the subject and felt I understood it to boot

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  • fairy
  • 03-13-18

interetsing and well done

This book indeed provided a gentle introduction to the world of Artificial Neural Networks. I am a veterinarian. My interest in how biological neurons carry out computations is what led me to this book. While my knowledge of biological neuro anatomy and physiology is strong, I have minimal computer science background and only recently acquired skills in python, linear algebra and calculus. This proved more than enough to navigate from cover to cover. I came out the other side having built, tested and refined my own neural network on my laptop. Understanding that these networks only solve problems as well as their constructor can make them, I can't say I'm an expert after just one build.Thanks for a great book. Well done.