Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and Their Role in Machine Learning and Artificial Intelligence

De: Herbert Jones

Narrado por: Sam Slydell

Duración: 3 h y 4 m

Resumen del Editor

If you want to learn about Neural Networks then keep reading....

Aladdin from The Arabian Nights had a magic lamp that fulfilled his every wish when rubbed. Today we have a smartphone that serves as a window to a whole universe of knowledge, entertainment, and even wise personal assistants, such as Siri - all we have to do is rub the screen. Aladdin’s lamp was powered by a genie, but what powers Siri?

Neural networks. It’s an astounding concept that tries to mimic the way living brains work by amalgamating human and machine ways of thinking.

The goal of this audiobook is to present the listener with a digestible explanation of neural networks while keeping the underlying concepts intact. The listener will acquire fundamental knowledge of neural networks through loosely related chapters that nonetheless reference terms and ideas mentioned throughout the audiobook.

The audiobook itself isn’t meant to be strictly academic, but a blend of colloquial and technical that brings this exciting, yet eerie, topic to the widest swath of the general public. There is a lot of coding and math behind neural networks, but the listener is presumed to have no prior knowledge or interest in either, so the concepts are broken down and elaborated on as such.

Each chapter is made as standalone as possible to allow the listener to skip back and forth without getting lost, with the glossary at the very end serving as a handy summary.

So if you want to learn about Neural Networks without having to go through heavy textbooks, listen to this audiobook now!

©2018 Herbert Jones (P)2018 Herbert Jones

Good Purchase

I feel it is a very good book over-all for Neural Networks. It is one of the very few books that I came across with an excellent description of Time Delay Neural Networks (TDNN) and the associated learning algorithms.

Happy With This

I bought this book a while ago, and I must say that it has been a source of immense help in deepening my understanding of neural networks. Yes, if you buy this, you will clearly realize that it has 'severe' amounts of math on every page, but again, if you can figure the math out, other aspects of the book (especially coverage) generally make it worth the deal.

Overall Good

The book is full of challenging and drill-like problems. The references cited blasts the door before the listener’s ears to explore worlds of applications. Author’s contribution to the field of Neural Networks is remarkable.

Just a high overview

This is fine for those who have no knowledge of AI or Neural NW but doesn’t go to any depth about how it works, only covers the threat of what it could do

Good One

This book does a very good job at that. In spite of its focus on mathematics and algorithms, the discussion is easy to follow with a working knowledge of linear algebra and optimization.

Very Well-Written

Finally, we have a book that combines intuition and mathematics to describe the analytical and methodological aspects of deep learning. The writing style makes it easy to follow complex material.

Fairly Balanced

This is a very well-written book on the theory and algorithms of deep learning. To really understand deep learning, it is important to know what goes on under the hood of DL models, and how they are connected to known machine learning models.

Great Audiobook

Great audiobook for graduate students. Broad overview and introduction to many relevant machine learning approaches in use or study today. Deep enough to enable the student to follow what prominent researchers have been publishing about machine learning.

All Five Stars

Excellent book ... excellent explanation.. This is a fantastic introduction to neural network ...I recommend this.

Enjoyed It

The best part of the book is that it gives a feel of what goes on under the surface. It concentrates on the algorithms and does not depend on specific implementation frameworks to build the concepts one needs.