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Build Recommendation Systems using Collaborative Filtering

IntermediateGuided Project

Python is a popular programming language that can be used to create recommendation systems. In this guided project, you will learn how to create a recommendation system based on collaborative filtering.

4.5 (18 Reviews)

Language

  • English

Topic

  • Machine Learning

Enrollment Count

  • 96

Skills You Will Learn

  • Correlation Functions, Recommendation Systems

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 25 minutes

Platform

  • SkillsNetwork

Last Update

  • May 3, 2024
About This Guided Project
Python is a popular programming language used in data science and analytics, as it provides a wide range of libraries and tools for working with data. You can use Python to create recommendation systems using collaborative filtering, which uses similar users’ preferences to generate recommendations.

In this guided project, you’ll learn how to use Python and the pandas library to create a recommendation system using collaborative filtering. 

You’ll begin by downloading a data set from GroupLens, then importing the necessary libraries, storing the data in DataFrames, and preprocessing the DataFrame to prepare the data for analysis. Finally, you’ll use this data to create a movie recommendation system using collaborative filtering, 

After completing this guided project, you’ll be ready to apply your new skills to use collaborative filtering to create recommendations using your own data sets and criteria.

A Look at the Project Ahead

After completing this project, you'll be able to:
  • Create a recommendation system based on collaborative filtering
 

What You'll Need

For this project, you will need:
  • Familiarity with basics of Python and pandas
  • A web browser

Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to the Python environment that we offer as part of the IBM Skills Network Labs environment. This platform works best with current versions of modern browsers. 

Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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