Byte-Sized ML Basic Series: Unsupervised Learning
- Created By raju2006
- Last Updated February 21st, 2025
- Overview
- Pre-Requisite
- Audience
- Curriculum
Session Description:
Cluster analysis is a vital component of unsupervised learning and data science. In this short session, we will explore the couple of unsupervised learning techniques – perform data clustering, reduce data dimensionality.
Setup:
Because this is an abbreviated session, attendees MUST install Anaconda software https://www.anaconda.com/ and have a basic understanding of using Jupyter Notebook.
Course Code/Duration:
BDT114 / 90 Minutes
Learning Objectives:
We will learn the following about the recommendation systems:
- Build a model to create clusters from data. Understand the intuition behind what principal component analysis (PCA).
- Build a simple PCA model to reduce dimensionality of data
Training material provided: Yes (Digital format)
- Learn basic understanding of python language, pandas library and understanding of how to use Juypter Notebook.
This session is designed for anyone who is familiar with basic steps involved in machine learning and are familiar with tools involved in building machine learning models.
The curriculum is empty
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