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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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Toc

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

Implementation of ANN

In this section, we will implement our first ANN in Python using numpy as our dependency. During this implementation, you can relate how gradient descent, activation function, and loss function have been integrated into our code. Apart from this, we will see the concept of backpropagation.

We will see the implementation of a single-layer NN with backpropagation.

Single-layer NN with backpropagation

Here, we will see the concept of backpropagation first, then we will start coding and I will explain things as we code.

Backpropagation

In a single-layer...

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