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Deep Learning By Example

You're reading from Deep Learning By Example

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788399906

Pages 450 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (18) Chapters

Preface

1. Data Science - A Birds' Eye View

2. Data Modeling in Action - The Titanic Example

3. Feature Engineering and Model Complexity – The Titanic Example Revisited

4. Get Up and Running with TensorFlow

5. TensorFlow in Action - Some Basic Examples

6. Deep Feed-forward Neural Networks - Implementing Digit Classification

7. Introduction to Convolutional Neural Networks

8. Object Detection – CIFAR-10 Example

9. Object Detection – Transfer Learning with CNNs

10. Recurrent-Type Neural Networks - Language Modeling

11. Representation Learning - Implementing Word Embeddings

12. Neural Sentiment Analysis

13. Autoencoders – Feature Extraction and Denoising

14. Generative Adversarial Networks

15. Face Generation and Handling Missing Labels

16. Implementing Fish Recognition

Code for fish recognition

17. Other Books You May Enjoy

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Capacity of a single neuron

A neural network is a computational model that is mainly inspired by the way the biological neural networks of the human brain process the incoming information. Neural networks made a huge breakthrough in machine learning research (deep learning, specifically) and industrial applications, such as breakthrough results in computer vision, speech recognition, and text processing. In this chapter, we will try to develop an understanding of a particular type of neural network called the multi-layer Perceptron.

Biological motivation and connections

The basic computational unit of our brains is called a neuron, and we have approximately 86 billion neurons in our nervous system, which are connected with...

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