Get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualization

 Key Features

Analyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensim

Implement common and not-so-common linguistic processing tasks using Python libraries

Overcome the common challenges faced while implementing NLP pipelines

 Book Description

Python is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization.