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Deep Learning with Keras

You're reading from Deep Learning with Keras Implementing deep learning models and neural networks with the power of Python

Product type Paperback

Published in Apr 2017

Publisher Packt

ISBN-13 9781787128422

Length 318 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (2):

Antonio Gulli

Sujit Pal

View More author details

Table of Contents (10) Chapters

Preface

1. Neural Networks Foundations FREE CHAPTER

2. Keras Installation and API

3. Deep Learning with ConvNets

4. Generative Adversarial Networks and WaveNet

5. Word Embeddings

6. Recurrent Neural Network — RNN

7. Additional Deep Learning Models

8. AI Game Playing

9. Conclusion

Keras 2.0 — what is new

Distributed representations

Distributed representations attempt to capture the meaning of a word by considering its relations with other words in its context. The idea is captured in this quote from J. R. Firth (for more information refer to the article: Document Embedding with Paragraph Vectors, by Andrew M. Dai, Christopher Olah, and Quoc V. Le, arXiv:1507.07998, 2015), a linguist who first proposed this idea:

You shall know a word by the company it keeps.

Consider the following pair of sentences:

Paris is the capital of France.Berlin is the capital of Germany.

Even assuming you have no knowledge of world geography (or English for that matter), you would still conclude without too much effort that the word pairs (Paris, Berlin) and (France, Germany) were related in some way, and that corresponding words in each pair were related in the same way to each other, that is:

Paris : France :: Berlin : Germany

Thus, the aim of distributed representations is to find a general transformation function...

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Authors (2)

Antonio Gulli

Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.

See other products by Antonio Gulli

Sujit Pal

Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

See other products by Sujit Pal

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