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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

Gradient descent-based optimization

In this section, we will discuss gradient descent-based optimization options that are provided by TensorFlow. Initially, it will not be clear which optimization option you should use, but as and when you know the actual logic of the DL algorithm, it will became much clearer to you.

We use a gradient descent-based approach to develop an intelligent system. Using this algorithm, the machine can learn how to identify patterns from the data. Here, our end goal is to obtain the local minimum and the objective function is the final prediction that the machine will make or result that is generated by the machine. In the gradient descent-based algorithm, we are not concentrating on how to achieve the best final goal for our objective function in the first step, but we will iteratively or repeatedly take small steps and select the intermediate best option...

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