by Dipanjan Sarkar (Author)
Leverage Natural Language Processing (NLP) fundamentals in Python and learn how to set up your own robust environment for performing text analytics. This updated version will show you how to use the latest state-of-the-art frameworks and how to work with text data in Python.
You'll explore several new topics, including working with Pythonfor NLP, illustrated with more hands-on examples. There are also new chapters on engineering text data (both traditional and newer deep learning based embedding methods) and deep learning for advanced text analytics and NLP.
While the overall structure of the book remains the same, the entire code base, modules, and frameworks will be updated to the latest Python 3.x release. You'll review new and improved methods for evaluating and interpreting classification models, and will look at newer lexicons and methodologies for unsupervised learning.
What You'll Learn
* Understand NPL and text syntax, semantics and structure* Discover text cleaning and feature engineering* Review text classification and text clustering * Assess text summarization and topic models* Study deep learning for NLP
Who This Book Is For
IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Format: Paperback
Pages: 698
Edition: 2nd ed.
Publisher: Apress
Published: 22 May 2019
ISBN 10: 1484243536
ISBN 13: 9781484243534
Dipanjan Sarkar is a Data Scientist at Intel, the world's largest silicon company which is on a mission to make the world more connected and productive. He primarily works on Analytics, Business Intelligence, Application Development and building large scale Intelligent Systems. He received his master's degree in Information Technology from the International Institute of Information Technology, Bangalore with a focus on Data Science and Software Engineering. He is also an avid supporter of self-learning, especially Massive Open Online Courses and holds a Data Science Specialisation from Johns Hopkins University on Coursera.
He has been an analytics practitioner for over six years, specializing in statistical, predictive and text analytics. He has also authored a books on R and Machine Learning and occasionally reviews technical books and acts as a course beta tester for Coursera. Dipanjan's interests include learning about new technology, financial markets, disruptive start-ups, data science and more recently, artificial intelligence and deep learning. In his spare time he loves reading, gaming and watching popular sitcoms and football.