Lab | Intro to Recommender Systems

Introduction

In the Intro to Recommender Systems lesson, we learned about collaborative filtering and walked through how to generate recommendations based on user similarity. In this lab, we will continue practicing how to create a user-based collaborative filtering recommender system in a step-by-step fashion.

Getting Started

Open the main.ipynb file in the your-code directory. There are a bunch of questions to be solved. If you get stuck in one exercise you can skip to the next one. Read each instruction carefully and provide your answer beneath it.

Deliverables

• main.ipynb with your responses to each of the exercises.

Submission

Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.

Resources

• Recommender Systems in Python
• How to build a Simple Recommender System in Python
• How Recommender Systems Work