Applied Artificial Intelligence for Business Leaders by Mariya Yao, Adelyn Zhou, and Marlene Jia is the book to get for anyone who wants to get a hand on how AI is shaping the business landscape today. Specifically, business owners who are interested in AI will find Applied Artificial Intelligence an excellent resource! It is a quick read and useful guide with densely packed information for business leaders looking to understand more about artificial intelligence for business, enterprise applications, and recommended implementation strategies. It helps the reader clarify a lot of AI terminology and clarify common errors with data and machine learning. It also comes highly recommended as an informative book suitable for both technical and non-technical business executives!

A few people in the ML scene have recommended this book. Statistics is a pretty important topic. Helping you work out how to improve and analyse your datasets. So learning more about the topic should not hurt.

What you will Learn: You'll learn the concepts behind neural networks and deep learning.

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Machine learning has bestowed humanity the power to run tasks in an automated manner. It allows improving things that we already do by studying a continuous stream of data related to that same task. Machine learning has a wide array of applications that belongs to different fields, ranging from space research to digital marketing. Machine learning also forms the basis of artificial intelligence. We're not yet flooded with machines capable of throwing judgments on their own. It's still a long way to reach there.

I've been learning machine learning for the past two years now, these books have all been instrumental throughout. The Hundred-Page Machine Learning Book (buy) - https://bit.ly/100pagemlbook The Deep Learning Book (buy) - https://amzn.to/2YIsGok The Hundred-Page Machine Learning Book Review - https://youtu.be/btLxTTkSZuY Get email updates on my work - https://bit.ly/mrdbourkenewsletter

In today's post I'm going to share with you the 7 best deep learning books (in no particular order) I have come across and would personally recommend you read. Some of these deep learning books are heavily theoretical, focusing on the mathematics and associated assumptions behind neural networks and deep learning. Other deep learning books are entirely practical and teach through code rather than theory. And even other deep learning books straddle the line, giving you a healthy dose of theory while enabling you to "get your hands dirty" and learn by implementing (these tend to be my favorite deep learning books). For each deep learning book I'll discuss the core concepts covered, the target audience, and if the book is appropriate for you.