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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

Basics of neural networks

The concept of neural networks is one of the oldest techniques in ML. Neural network is derived from the human brain. In this section, we will see the human brain's components and then derive the ANN.

In order to understand ANN, we first need to understand the basic workflow of the human brain. You can refer to Figure 9.11:

Figure 9.11: Neurons of human brain (Image credit: https://en.wikipedia.org/wiki/File:Blausen_0657_MultipolarNeuron.png)

The human brain consists of an estimated hundreds of billion nerve cells called neurons. Each neuron performs three jobs that are mentioned as follows:

  • Receiving a signal: It receives a set of signals from its dendrites
  • Deciding to pass the signal to the cell body: It integrates those signals together to decide whether or not the information should be passed on to the cell body
  • Sending the signal: If some...
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