Published 07/2022
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Difficulty: Intermediate | Genre: eLearning | Language: English + srt | Duration: 5 Lectures (38m) | Size: 939.8 MB
This course covers the basic techniques you need to know in order to fit a Natural Language Processing Machine Learning pipeline using scikit-learn, a machine learning library for Python.
Learning Objectives
Learn about the two main scikit-learn classes for natural language processing: CountVectorizer and TfidfVectorizer
Learn how to create Bag-of-Words (boW) representations and TF-IDF representations
Learn how to create a machine learning pipeline to classify BBC news articles into different categories
Intended Audience
This course is intended for anyone who wishes to understand how NLP works and, more particularly, how to implement it using scikit-learn.
Prerequisites
To get the most out of this course, you should already have an understanding of the Python programming language.
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