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Hands-On Neural Networks with Keras

You're reading from Hands-On Neural Networks with Keras Design and create neural networks using deep learning and artificial intelligence principles

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789536089

Length 462 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Artificial Intelligence

Author (1):

Niloy Purkait

View More author details

Table of Contents (16) Chapters

Preface

1. Section 1: Fundamentals of Neural Networks FREE CHAPTER

2. Overview of Neural Networks

3. A Deeper Dive into Neural Networks

4. Signal Processing - Data Analysis with Neural Networks

5. Section 2: Advanced Neural Network Architectures

6. Convolutional Neural Networks

7. Recurrent Neural Networks

8. Long Short-Term Memory Networks

9. Reinforcement Learning with Deep Q-Networks

10. Section 3: Hybrid Model Architecture

11. Autoencoders

12. Generative Networks

13. Section 4: Road Ahead

14. Contemplating Present and Future Developments

15. Other Books You May Enjoy

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A Deeper Dive into Neural Networks

In this chapter, we will encounter more in-depth details of neural networks. We will start from building a perceptron. Moving on, we will learn about activation functions. And we will also be training our first perceptron.

In this chapter, we will cover the following topics:

From the biological to the artificial neuron – the perceptron
Building a perceptron
Learning through errors
Training a perceptron
Backpropagation
Scaling the perceptron
A single layered network

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Authors (1)

Purkait

Purkait

Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments. He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.

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