Text Mining with Machine Learning and Python – Teaching text mining and learning machine with Python
Text is one of the most actively explored and widely spread data types in the field of Data Science today. New advances in machine learning and deep learning techniques make it possible to build fantastic data products on text sources. New exciting text data sources pop up all the time. You will build your own toolbox of know-how, packages, and work code snippets so you can perform your own text mining analyzes.
You will begin by understanding the fundamentals of modern text mining and moving to some of the exciting processes involved in it. You will learn how machine learning is used to extract meaningful information from the text and the various processes involved in it. You will learn to read and process text features. Then you’ll learn how to extract information from text and work on pre-trained models, while also delving into text classification, and entity extraction and classification. You will explore the process of word embedding by working on Skip-grams, CBOW, and X2Vec with some extra and important text mining processes. By the end of the course, you will have learned and understood the various aspects of text mining with ML and the important processes involved in it, and will begin your journey as an effective text miner.
Table of Contents:
– Getting Started with Text Mining
– Reading and Processing Text Features
– Extracting from Text
– Classification of Text
– Word Embeddings
– Other ML Topics with Text
Manufacturer: Pocket Publishing / Packt Publishing
Language of instruction: English
Teacher: Thomas Dehaene
Level of training: Elementary, Secondary
Time of training: 2 hours + 30 minutes
File size: 281 MB