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You're reading from Hands-On Neural Networks Learn how to build and train your first neural network model using Python

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781788992596

Length 280 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Neural Networks

Authors (2):

Leonardo De Marchi

Laura Mitchell

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Table of Contents (16) Chapters

Preface

1. Section 1: Getting Started FREE CHAPTER

2. Getting Started with Supervised Learning

3. Neural Network Fundamentals

4. Section 2: Deep Learning Applications

5. Convolutional Neural Networks for Image Processing

6. Exploiting Text Embedding

7. Working with RNNs

8. Reusing Neural Networks with Transfer Learning

9. Section 3: Advanced Applications

10. Working with Generative Algorithms

11. Implementing Autoencoders

12. Deep Belief Networks

13. Reinforcement Learning

14. Whats Next?

15. Other Books You May Enjoy

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Summary

In this chapter, we have explained what autoencoders are and discussed their various types. Throughout, we have given coded examples as to how autoencoders can be applied to the MNIST dataset.

In the next chapter, we will introduce Deep Belief Networks (DBNs) along with some fundamental concepts that underpin their architecture.

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Authors (2)

Leonardo De Marchi

Leonardo De Marchi is an international speaker, author and consultant. He holds a masters in artificial intelligence (AI) and has worked as a data scientist in the sporting world, with clients such as New York Knicks, Manchester United. He now works as a head of data scientist at Badoo, the largest dating site with over 400 million users. He is also the lead instructor at ideai.io, a company specialized in Machine Learning trainings. With Ideai he provides technical and managerial training to large institutions and dynamic startups. He is also a contractor for the European Commission.

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Laura Mitchell

Laura Mitchell graduated with a degree in mathematics from the University of Edinburgh and, since then, has gained over 12 years' experience in the tech and data science space. She is currently lead data scientist at Badoo, which is the largest online dating site in the world with over 400 million users worldwide. Laura has hands-on experience in the delivery of projects such as NLP, image classification, and recommender systems, from initial conception through to production. She has a passion for learning new technologies and keeping up to date with industry trends.

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