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Hands-On Natural Language Processing with Python

Hands-On Natural Language Processing with Python

By : Shanmugamani, Arumugam, Byiringiro, Joshi, Muthuswamy
2.8 (4)
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Hands-On Natural Language Processing with Python

Hands-On Natural Language Processing with Python

2.8 (4)
By: Shanmugamani, Arumugam, Byiringiro, Joshi, Muthuswamy

Overview of this book

Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts.
Table of Contents (15 chapters)
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6
Searching and DeDuplicating Using CNNs
7
Named Entity Recognition Using Character LSTM
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Named Entity Recognition Using Character LSTM

Human beings, when provided with repetitive tasks, are prone to committing errors, owing to muscle memory and loss of concentration. Loss of concentration is often known as brain fatigue, wherein the brain tends to operate in an autopilot state, without the need to think about actions and reactions. Hence, there is a pressing need to improve conventional user interfaces, changing the way that we fundamentally interact with machines, to cater to answer questions without any loss of information or errors. Such user interfaces are also a very important area of research, owing to their impact on a multitude of applications, in customer service, search interfaces, and human-computer interactions.

In order to develop such interfaces, one of the fundamental tasks is to understand and interpret a sentence provided as input by a user. Such...

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