Mueller J.P., Massaron L. Deep Learning for Dummies

John Wiley & Sons, Inc, 2019. — 442 p. — ISBN: 978-1-119-54304-6.Take a deep dive into deep learning.
Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic — and all of the underlying technologies associated with it.
In no time, you’ll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then provides examples of the major deep learning application types.The first part of this book gives you some starter information so that you don’t get completely lost before you start. You discover how to install the various products you need and gain an understanding of some essential math. The beginning examples are more along the lines of standard regression and machine learning, but you need this basis to gain a full appreciation of just what deep learning can do for you.
After you get past these initial bits of information, you start to do some pretty amazing things. For example, you discover how to generate your own art and perform other tasks that you might have assumed to require many of coding and some special hardware to accomplish. By the end of the book, you’ll be amazed by what you can do, even if you don’t have an advanced machine learning or deep learning degree.Includes sample code
Provides real-world examples within the approachable text
Offers hands-on activities to make learning easier
Shows you how to use Deep Learning more effectively with the right tools
This book is perfect for those who want to better understand the basis of the underlying technologies that we use each and every day.Discovering Deep Learning
Introducing Deep Learning
Introducing the Machine Learning Principles
Getting and Using Python
Leveraging a Deep Learning Framework
Considering Deep Learning Basics
Reviewing Matrix Math and Optimization
Laying Linear Regression Foundations
Introducing Neural Networks
Building a Basic Neural Network
Moving to Deep Learning
Explaining Convolutional Neural Networks
Introducing Recurrent Neural Networks
Interacting with Deep Learning
Performing Image Classification
Learning Advanced CNNs
Working on Language Processing
Generating Music and Visual Art
Building Generative Adversarial Networks
Playing with Deep Reinforcement Learning
The Part of Tens
Ten Applications that Require Deep Learning
Ten Must-Have Deep Learning Tools
Ten Types of Occupations that Use Deep Learning