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Deep Learning with Theano

You're reading from   Deep Learning with Theano Perform large-scale numerical and scientific computations efficiently

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781786465825
Length 300 pages
Edition 1st Edition
Tools
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Author (1):
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Christopher Bourez Christopher Bourez
Author Profile Icon Christopher Bourez
Christopher Bourez
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Table of Contents (15) Chapters Close

Preface 1. Theano Basics FREE CHAPTER 2. Classifying Handwritten Digits with a Feedforward Network 3. Encoding Word into Vector 4. Generating Text with a Recurrent Neural Net 5. Analyzing Sentiment with a Bidirectional LSTM 6. Locating with Spatial Transformer Networks 7. Classifying Images with Residual Networks 8. Translating and Explaining with Encoding – decoding Networks 9. Selecting Relevant Inputs or Memories with the Mechanism of Attention 10. Predicting Times Sequences with Advanced RNN 11. Learning from the Environment with Reinforcement 12. Learning Features with Unsupervised Generative Networks 13. Extending Deep Learning with Theano Index

Metrics for natural language performance


The Word Error Rate (WER) or Character Error Rate (CER) is equivalent to the designation of the accuracy error for the case of natural language.

Evaluation of language models is usually expressed with perplexity, which is simply:

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