Text Mining with Machine Learning and Python Free Download
7 Likes Comment

Text Mining with Machine Learning and Python, FreeTuts Download

Text Mining with Machine Learning and Python, FreeTuts Download

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.

Screenshot Tutorials/Courses

Text Mining with Machine Learning and Python, FreeTuts Download

Info Tutorials/Courses

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

Go to Download Tutorials Page

Password : freetuts.download

You might like

About the Author: Ho Quang Dai

I am Ho Quang Dai. Looking forward to receiving positive contributions from readers

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.