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Medium⏱ time2.5 hr$ cost0

Movie Recommender

Suggest films a user might like based on what similar users enjoyed.

Start building ↓
fig — working model Result first

The build

Step 01

Load ratings

Read a table of users and movie scores.

Step 02

Find neighbours

Compute which users rate alike.

Step 03

Predict tastes

Recommend films liked by similar users.

Step 04

Show picks

List top suggestions for a user.

Working Principle

The system finds users with similar rating patterns and recommends movies they liked but the target user hasn't seen yet.

The science behind it

A closer look

Collaborative filtering uses 'people like you also liked' logic; similarity is measured between users' rating vectors.

Take it further

Variables to test

  • 1 Switch to item-based similarity — better picks?
  • 2 How does a brand-new user fare (cold start)?
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