Natural Language Processing Fundamentals: Build Intelligent Applications That Can Interpret The Human Language to Deliver Impactful Results
Publisher,Packt Publishing
Publication Date,
Format,
Weight,
No. of Pages, 374
Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems.
Key Features
- Assimilate key NLP concepts and terminologies
- Explore popular NLP tools and techniques
- Gain practical experience using NLP in application code
Book Description
If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems.
You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots.
By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.
What you will learn
- Obtain, verify, and clean data before transforming it into a correct format for use
- Perform data analysis and machine learning tasks using Python
- Understand the basics of computational linguistics
- Build models for general natural language processing tasks
- Evaluate the performance of a model with the right metrics
- Visualize, quantify, and perform exploratory analysis from any text data
Who this book is for
Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.
Table of Contents
- General Introduction to NLP
- Extraction Methods from Unstructured Text
- Building a Simple Classifier
- Collecting Text Data
- Topic Modelling
- Text Summarization and Text Generation
- Vector Representation
- Sentiment Analysis
-
Language Detection using Neural Networks
About the Author
Sohom Ghosh is a passionate data detective with expertise in Natural Language Processing. He has worked extensively in the Data Science arena with specialization in Deep Learning based Text Analytics, NLP & Recommendation Systems.He has publications in several international conferences and journals.
Dwight Gunning is a data scientist at FINRA, a financial services regulator in the US. He has extensive experience in Python-based machine learning and hands-on experience with the most popular NLP tools such as NLTK, gensim, and spacy.
