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The Math of Neural Networks eBook Michael Taylor Mark Koning

Download As PDF : The Math of Neural Networks eBook Michael Taylor Mark Koning

The Math of Neural Networks eBook Michael Taylor Mark Koning

"The Math of Neural Networks" by Michael Taylor would probably get four or five stars except for one reason: it is the same book as "Make Your Own Neural Network: An In-depth Visual Introduction For Beginners" except with a few chapters missing. You don't need to buy this book. If you want all of the information, buy the other book by the same author for the same price. This book is a rip-off.


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The Math of Neural Networks eBook Michael Taylor Mark Koning Reviews

This book is essentially about what is called the neural network. Before reading this book, I did not know what to expect, and I did not even know what a neural network was. However, after reading, I now have more of an understanding. Personally, I thought the topic was very complex. However, the author did a great job of simplifying the concept and process. The author presented the material in such a way that was fun to learn. There is a lot of research in this book, making it extremely fact heavy and educational. I definitely felt as if I had to sit and focus on the reading more than if I were reading a fiction book. This book does seem as if it is a good resource book for anyone involved in this type of material. Overall, this is a great book for anyone who is interested in educational mathematics and learning about neural networks.
The Math of Neural Networks by M. Taylor is a good book for people who don’t already have more than a beginners knowledge of neural networks, though they should have a working knowledge of matrices, vertices, and derivatives. Taylor does a good job of breaking down a complex subject, but it’s not something you will read and fully comprehend in one sitting. It will take time and effort to fully digest the content of this book, especially if you are a beginner as the book was designed for. I love Math so looking at the formulas that are behind neural networks was interesting for me. I will definitely need to reread the content a few times in order to assimilate it and be able to use it. That said, the work will be worth the effort as it will give me knowledge that I didn’t have before.
The Math of Neural Networks A Visual Introduction for Beginners by Michael Taylor is a comprehensive book that details and explains neural networking. It is more than advisable to have done some research on neural networks prior to reading this book, as it is a complex subject and requires a basic understanding. This book is not to be read in one short sitting, but digested slowly, and re-read to fully comprehend the subject matter at hand. Taylor has done a good job of breaking down the information, and if you are a novice, has simplified the language and presentation somewhat to make it more accessible. Anyone who wants to learn more about Deep learning and artificial intelligence will benefit from reading this book. Highly recommend.
The Math of Neural Networks is a book for beginners who plan on using the information in a website enhancement or other computer endeavor.  I was not acquainted with neural networks before reading this book but had taken statistics and alegbra. I never realized how much math was involved in doing some of the simplest things. The author does a good job of making it plain so that I could get the gist of the concepts although I am not really interested in it. There are several charts and a glossary which I found very helpful. 

The book has a pretty lengthy bibliography that definitely showed me the author had done extensive research to back up the info provided. There were so many terms like hyperparameters, bias value and momentum that I was thankful the author goes in depth to describe. I think that if I was truly interested in the computer science field or worked in that capacity this would be a good reference to read. 
This is my second book on neural networks and it supports the knowledge base of the first one in a nice way. That said, if you don’t have at least a basic education of math functions and statistics, it will be difficult for you to follow the chapters and extract as much as possible out of them. The author does state what is the recommended audience for his book, so, in case you are out of the scope of it, you should maybe try and get your hands on his first one, because many things will be easier to grasp in this way. Advanced-level readers of this book will definitely find worthwhile information in the calculation methods and in the practical solutions for machine learning. Also, a lot of useful information on the two basic math functions used in nodes, as well as how these fit within the network. There is a nice summary of referenced content at the end that provides extra reading materials for aspiring users. Bonus for the simple way of explaining things, a skill many tech pros miss.
This is an excellent stand-alone book, though if you are a complete novice to the basics of what a neural network is and how it works, I would recommend first starting with Taylor’s other book, “Make Your Own Neural Network An In-depth Visual Introduction For Beginners” which will walk you through creating your first neural network, step by step, down to explaining each line of code (using Python, but no prior knowledge is assumed).

If you have at least a vague idea already of what a neural network is and how it works even if just in principle, then by all means dive right into this book which focusses, as the title suggests, on the mathematics of neural networks.

However! This is not a dry maths textbook, and the explanations keep it tied closely to the topic at hand with examples aplenty, and in the same style as Taylor’s other work, very lucid step-by-step visual walkthroughs of everything, explaining each part quickly but without assuming prior mathematical knowledge (beyond perhaps the basest of concepts; nothing that should challenge anyone who has even just a high-school level understanding of maths, or perhaps even a not quite that).

All in all, this is an incredibly accessible and illuminating book that I highly recommend to any who have an interest in the under-the-hood aspects of machine learning.
"The Math of Neural Networks" by Michael Taylor would probably get four or five stars except for one reason it is the same book as "Make Your Own Neural Network An In-depth Visual Introduction For Beginners" except with a few chapters missing. You don't need to buy this book. If you want all of the information, buy the other book by the same author for the same price. This book is a rip-off.