From the last one year, you may have heard this kind of question. In the AI world, these kinds of questions have become common. People have created a hype that AI will make humanity vanish and machines will take away all the powers from us. Now let me tell you, this is not the truth. These kinds of threats sound like science-fiction stories. According to me, AI is in its high pace development phase but its purpose is to complement humanity and make human life easier. We are still figuring out some of the complex and unknown truths of this universe that can help us provide more insight on how we can build AI-enabled systems. So AI is purely going to help us. AI will amaze our lives for sure but it is not going to be saturated with its inventions soon. So enjoy this AI phase and contribute to the AI ecosystem in a positive manner...
Python Natural Language Processing
Python Natural Language Processing
Overview of this book
This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them.
During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis.
You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data.
By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world.
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Current Title:
Python Natural Language Processing
Table of Contents (13 chapters)
Preface
Free Chapter
Introduction
Practical Understanding of a Corpus and Dataset
Understanding the Structure of a Sentences
Preprocessing
Feature Engineering and NLP Algorithms
Advanced Feature Engineering and NLP Algorithms
Rule-Based System for NLP
Machine Learning for NLP Problems
Deep Learning for NLU and NLG Problems
Advanced Tools
How to Improve Your NLP Skills
Customer Reviews