AI/ML Byte-Sized Series: Recommendation Systems
- Created By raju2006
- Last Updated December 4th, 2023
- Overview
- Prerequisites
- Audience
- Audience
- Curriculum
Description:
A short course on understanding what are recommendation systems. Understand different types of recommendation systems and the tools used to build them.
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:
BDT113 / 90 Minutes
Learning Objectives:
We will learn the following about the recommendation systems:
- Types of recommendation systems
- Different metrics that are used to measure recommendation systems
- List different ways of creating a recommendation system
- Simple example of content-based recommendation system.
- Basic understanding of Python
- Anyone interested in Machine Learning and Recommendation Systems
- Anyone interested in Machine Learning and Recommendation Systems
Course Outline:
- Introduction to Recommendation Systems
- Overview of recommendation systems and their role in enhancing user experiences.
- Collaborative and Content-Based Filtering
- Understanding the principles and implementation of collaborative and content-based recommendation approaches.
III. Hybrid Recommendation Systems
- Integration of collaborative and content-based methods for improved recommendation.
- accuracy.
- Evaluation Metrics and Real-world Applications
Training Material Provided: Yes (Digital Format)
The curriculum is empty
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