Introduction

Text Analysis with Python: A Research-Oriented Guide is a quick and comprehensive reference on text mining using python code. The main objective of the book is to equip the reader with the knowledge to apply various machine learning and deep learning techniques to text data. The book is organized into eight chapters which present the topic in a structured and progressive way.

Key Features:

• - Introduces the reader to Python programming and data processing
• - Introduces the reader to the preliminaries of natural language processing (NLP)
• - Covers data analysis and visualization using predefined python libraries and datasets
• - Teaches how to write text mining programs in Python
• - Includes text classification and clustering techniques
• - Informs the reader about different types of neural networks for text analysis
• - Includes advanced analytical techniques such as fuzzy logic and deep learning techniques
• - Explains concepts in a simplified and structured way that is ideal for learners
• - Includes References for further reading

Text Analysis with Python: A Research-Oriented Guide is an ideal guide for students in data science and computer science courses, and for researchers and analysts who want to work on artificial intelligence projects that require the application of text mining and NLP techniques.

Audience: Students in data science and computer science courses, and for researchers and analysts who want to work on artificial intelligence projects that require the application of text mining and NLP techniques.