The Unsupervised Learning Workshop

This is the repository for The Unsupervised Learning Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.

Requirements and Setup

To get started with the project files, you’ll need to:

1. Install Python on Windows/Mac/Linux
2. Install Anaconda on Windows/Mac/Linux

About The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You’ll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

What you will learn

• Distinguish between hierarchical clustering and the k-means algorithm
• Understand the process of finding clusters in data
• Grasp interesting techniques to reduce the size of data
• Use autoencoders to decode data
• Extract text from a large collection of documents using topic modeling
• Create a bag-of-words model using the CountVectorizer

Related Workshops

If you’ve found this repository useful, you might want to check out some of our other workshop titles:

• The Reinforcement Learning Workshop
• The Applied AI and Natural Language Processing Workshop
• The Deep Learning Workshop