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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

Rule-based machine translation

Classic rule-based machine translation systems heavily rely on rules for converting text from the source language to the target language. These rules, often created by linguists, generally work at the syntactic, semantic, and lexical levels. A classical rule-based machine translation system typically has three phases:

  • The analysis phase
  • The lexical transfer phase
  • The generation phase

Illustrated in Figure 3.1 is a flow diagram of a typical rule-based machine translation system:

Figure 3.1: A flow diagram of a rule-based machine translation system

The analysis phase

The first phase in rule-based machine translation is the analysis phase, in which the source language text is analyzed to extract...

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