User-Based Collaborative Filtering In Python | Machine Learning
User-based collaborative filtering is also called user-user collaborative filtering. It is a type of recommendation system algorithm that uses user similarity to make product recommendations.
In this tutorial, we will talk about
What is user-based (user-user) collaborative filtering?
How to create a user-product matrix?
How to process data for user-based collaborative filtering?
How to identify similar users?
How to narrow down the items pool?
How to rank items for the recommendation?
How to predict the rating score?
👉 What is user-based (user-user) collaborative filtering?
👉 How to create a user-product matrix?
👉 How to process data for user-based collaborative filtering?
👉 How to identify similar users?
👉 How to narrow down the items pool?
👉 How to rank items for the recommendation?
👉 How to predict the rating score?
⏰ Timecodes ⏰
0:00 - Intro
0:38 - Step 0: User-Based Collaborative Filtering Recommendation Algorithm
1:45 - Step 1: Import Python Libraries
2:02 - Step 2: Download And Read In Data
3:34 - Step 3: Exploratory Data Analysis (EDA)
4:46 - Step 4: Create User-Movie Matrix
5:04 - Step 5: Data Normalization
5:22 - Step 6: Identify Similar Users
6:54 - Step 7: Narrow Down Item Pool
7:42 - Step 8: Recommend Items
8:09 - Step 9: Predict Scores (Optional)
8:36 - Summary
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