Machine Learning

The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

By: Herbert Jones

Narrated by: Timothy Burke, Sam Slydell

Three comprehensive manuscripts in one audiobook.

• Machine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More
• Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and Their Role in Machine Learning and Artificial Intelligence
• 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

Here are some of the topics that are discussed in part one of this audiobook:

• What is machine learning?
• What’s the point of machine learning?
• History of machine learning
• Neural networks
• Matching the human brain
• Artificial intelligence
• AI in literature
• Talking, walking robots
• Self-driving cars
• Personal voice-activated assistants
• Data mining
• Social networks
• Big Data
• Shadow profiles
• Biometrics
• Self-replicating machines
• And much, much more!

Here are some of the topics that are discussed in part two of this audiobook:

• Programming a smart(er) computer
• Composition
• Self-driving neural networks
• Taking everyone’s job
• Quantum leap in computing
• Attacks on neural networks
• Neural network war
• Ghost in the machine
• No backlash
• And much, much more

Here are some of the topics that are discussed in part three of this audiobook:

• Improving the scientific method
• How it all started
• Appeasing the rebellious spirits
• Evolving the machine brain
• The future of deep learning
• Medicine with the help of a digital genie
• And much, much more

So listen to this audiobook now if you want to learn more about machine learning!

©2018 Herbert Jones (P)2018 Herbert Jones

Can't recommend it enough

The writer is well-established and a top person in data mining and machine learning and more topic. He also has written many other great audiobooks over the years.

A Thorough Book

This book goes into depth on many of the most used learning techniques via mathematics, and does a comprehensive look at the math behind each technique

Good Source

This book is particularly good in terms of grabbing the insights and intuitions underneath the different methods. It covers a vast majority of different techniques, and trying to present the ideas and intuitions why this method works or how this method is an implementation of a simpler idea, e.g.various obvious or hidden implementations of lasso regularization.

I loved it

This book is fairly deep given it's breadth, which is why it's so long. It's a very good book and an amazing reference but I do not recommend it unless you have strong mathematical maturity.

Real Educational Book

This book is amazing. I have read it thoroughly and I feel prepared to begin reading research papers on this topic. The only complaint I have is that the cover had a medium sized dent in the front when I got it, but its the content that matters

Awesome Explanations

I imagine anyone not especially interested in the theory of machine learning will be frustrated and turned off by this book. For everyone else, buckle up

Just watch a dozen YouTube videos instead

Pretty low level and at times naive interpretations of covered topics. Facebook topics were decent.

Excellent machine learning book.

I’m a beginner and this audiobook explains things in a way easy enough for me to know and get started with.

Very Enriching

This is a good book for those who use statistics for data mining. It seems that there is more accent on probabilistic (frequentist) field. Though a reader is expected to have good enough level in math’s to grasp the concepts quickly. May not be appropriate for the beginners in the field.

Another great audiobook

With the guidance of this audiobook helped me understand M.I. In a calm and logical progression. Thank you much.