Overview

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications.  Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts.  The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application.  What You'll Learn Grasp the basic process of neural networks through projects, such as creating music Restore and colorize black and white images with deep learning processes Who This Book Is For Beginners new to TensorFlow and Python. 

Full Product Details

Author:   Vinita Silaparasetty
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.682kg
ISBN:  

9781484258019

ISBN 10:   1484258010
Pages:   421
Publication Date:   25 July 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1— Perceptrons • Introduction to Perceptrons • Working of a Perceptron • Program to understand the working of a Perceptron Chapter 2: Neural Networks • Introduction to Neural Networks • Types of Neural Networks • How each neural network works • Program to understand the working of Neural Networks Chapter 3: Project 1- DJ Neuron • About the Project: Creating Music Using Neural Networks  • Requirements • Explanation of concepts used • Architecture of the Neural Network • Source code with line by line instructions  Chapter 4: Project 2- Artistic Neurons • About the Project: Adding colour to black and white images  • Requirements • Explanation of concepts used • Architecture of the Neural Network • Source code with line by line instructions  Chapter 5: Project 3- Go HD • About the Project: Restoration of images for better quality  • Requirements • Explanation of concepts used • Architecture of the Neural Network • Source code with line by line instructions Chapter 6: Project 4- Voice Experiments • About the Project: Voice Manipulation  • Requirements • Explanation of concepts used • Architecture of the Neural Network • Source code with line by line instructions Chapter 7: Project 5- Imposters • About the Project: Fake Image Recognition  • Requirements • Explanation of concepts used • Architecture of the Neural Network • Source code with line by line instructions  Chapter 8: Project 6 - Gaming is Fun • About the Project: MI-agent training using Unity. Learn to create Artificially Intelligent Characters. Requirements Explanation of concepts used Architecture of the Neural Network Source code with line by line instructions

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Author Information

Vinita Silaparasetty is a Data Scientist at Trendwise Analytics. Deep Learning is a topic she's passionate about, and she has experience working on deep learning projects and experimenting with neural networks. She aspires to share her love for deep learning with beginners and make it simple and easy to understand, so as to ignite a similar passion in them.

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