Deep Learning for Beginners

4.5 (2 reviews total)
By Dr. Pablo Rivas
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    Section 1: Getting Up to Speed

About this book

With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning. This book is designed to help you if you're a beginner looking to work on deep learning and build deep learning models from scratch, and you already have the basic mathematical and programming knowledge required to get started.

The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples, and learn how to build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you've learned through the course of the book.

By the end of this book, you'll be well-versed with deep learning concepts and have the knowledge you need to use specific algorithms with various tools for different tasks.

Publication date:
September 2020
Publisher
Packt
Pages
432
ISBN
9781838640859

 
Section 1: Getting Up to Speed

This section brings you up to speed on the basic concepts of learning from data, deep learning frameworks, and preparing data to be usable in deep learning.

This section consists of the following chapters:

About the Author

  • Dr. Pablo Rivas

    Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.

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Latest Reviews

(2 reviews total)
Excellent, introduces both shallow neural networks and deep neural networks, and has concrete examples using Python libraries for deep learning, such as TensorFlow
Je n'ai pas encore débuté la lecture, mais le contenu me semble très bien et accessible.

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