Processing Text with Python Essential Training

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Kumaran Ponnambalam

33:31

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01 - Introduction

01 - The need for text mining skills in data science.mp4

00:58

02 - 1. Text Mining

01 - Text mining today.mp4

01:30

02 - Document concepts.mp4

01:25

03 - Corpus concepts.mp4

01:08

04 - Introduction to the NLTK library.mp4

01:15

05 - Setting up the environment.mp4

01:52

03 - 2. Reading Text

01 - Reading raw files.mp4

01:28

02 - Reading files with corpus reader.mp4

01:09

03 - Exploring the corpus.mp4

01:56

04 - Analyzing the corpus.mp4

00:56

04 - 3. Text Cleansing and Extraction

01 - Tokenization.mp4

01:22

02 - Cleansing text.mp4

01:58

03 - Stop word removal.mp4

01:29

04 - Stemming.mp4

01:24

05 - Lemmatization.mp4

01:31

05 - 4. Advanced Text Processing

01 - Building n-grams.mp4

02:09

02 - Tagging parts of speech.mp4

01:30

03 - Term frequency-inverse document frequency (TF-IDF).mp4

02:34

04 - Building a TF-IDF matrix.mp4

02:11

06 - 5. Best Practices

01 - Storing text.mp4

01:06

02 - Processing text data.mp4

01:07

03 - Scalable processing of text data.mp4

01:03

07 - Conclusion

01 - Next steps.mp4

00:30

Description

In the world of big data, more and more information is consumed and analyzed in text form. Websites, social media, emails, and chats have become the key sources for data and insights. If you work with data, then understanding how to deal with unstructured text data is essential. In this course, instructor Kumaran Ponnambalam helps you build your text mining skill set, covering key techniques for extracting, cleansing, and processing text in Python. Kumaran reviews key text processing concepts like tokenization and stemming. He also looks at techniques for converting text into analytics-ready form, including n-grams and TF-IDF. Along the way, he provides examples of these techniques using Python and the NLTK library.

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Python

Machine Learning

Artificial Intelligence

Kumaran Ponnambalam

Instructor's Courses

A seasoned veteran in everything data, with a reputation for delivering high performance database and SaaS applications and currently specializing in leading Big Data Science and Engineering efforts

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