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Intelligent Projects Using Python

You're reading from   Intelligent Projects Using Python 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788996921
Length 342 pages
Edition 1st Edition
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Author (1):
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Santanu Pattanayak Santanu Pattanayak
Author Profile Icon Santanu Pattanayak
Santanu Pattanayak
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Table of Contents (12) Chapters Close

Preface 1. Foundations of Artificial Intelligence Based Systems FREE CHAPTER 2. Transfer Learning 3. Neural Machine Translation 4. Style Transfer in Fashion Industry using GANs 5. Video Captioning Application 6. The Intelligent Recommender System 7. Mobile App for Movie Review Sentiment Analysis 8. Conversational AI Chatbots for Customer Service 9. Autonomous Self-Driving Car Through Reinforcement Learning 10. CAPTCHA from a Deep-Learning Perspective 11. Other Books You May Enjoy

Creating a word vocabulary for the captions

In this section, we create the word vocabulary for the video captions. We create some additional words that are required as follows:

eos => End of Sentence
bos => Beginning of Sentence
pad => When there is no word to feed,required by the LSTM 2 in the initial N time steps
unk => A substitute for a word that is not included in the vocabulary

The LSTM 2, in which a word is an input, would require these four additional symbols. For the (N+1) time step, when we start generating the captions, we feed the word of the previous time step wt-1. For the first word to be generated, there is no valid previous time step word, and so we feed the dummy word <bos>, which signifies the start of sentence. Similarly, when we reach the last time step, wt-1 is the last word of the caption. We train the model to output the final word as &lt...

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