English | 2019 | ISBN: 1789954043 | 374 Pages | PDF | 377 MB
Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems.
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