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Python Natural Language Processing

You're reading from   Python Natural Language Processing Advanced machine learning and deep learning techniques for natural language processing

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121423
Length 486 pages
Edition 1st Edition
Languages
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Practical Understanding of a Corpus and Dataset 3. Understanding the Structure of a Sentences 4. Preprocessing 5. Feature Engineering and NLP Algorithms 6. Advanced Feature Engineering and NLP Algorithms 7. Rule-Based System for NLP 8. Machine Learning for NLP Problems 9. Deep Learning for NLU and NLG Problems 10. Advanced Tools 11. How to Improve Your NLP Skills 12. Installation Guide

Deep Learning for NLU and NLG Problems

We have seen the rule-based approach and various machine learning techniques to solve NLP tasks in the previous chapters. In this chapter, we will see the bleeding edge subset of machine learning technique called deep learning (DL). In the past four to five years, neural networks and deep learning techniques have been creating a lot of buzz in the artificial intelligence area because many tech giants use these cutting-edge techniques to solve real-life problems, and the results from these techniques are extremely impressive. Tech giants such as Google, Apple, Amazon, OpenAI, and so on spend a lot of time and effort to create innovative solutions for real-life problems. These efforts are mostly to develop artificial general intelligence and make the world a better place for human beings.

We will first understand the overall AI, in general...

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