Movie Recommendation System

Movie Recommendation System

Assessment

Interactive Video

Engineering, Information Technology (IT), Architecture, Performing Arts

University

Hard

Created by

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The video tutorial explains how to build an item-based collaborative filtering recommendation system for movies. It starts with creating a dummy rating matrix, standardizing user ratings, and calculating movie similarities using cosine similarity. The tutorial then demonstrates how to make movie recommendations based on user input and improve accuracy by adjusting similarity scores. Finally, it summarizes the steps to finalize the recommendation system.

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10 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the primary approach used in this project to recommend movies?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the structure of the dummy rating matrix created for the project.

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OFF

3.

OPEN ENDED QUESTION

3 mins • 1 pt

What issue arises from replacing non-values with zero in the rating matrix?

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OFF

4.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how the function to standardize ratings works.

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OFF

5.

OPEN ENDED QUESTION

3 mins • 1 pt

What metric is used to calculate similarity between movies in this project?

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OFF

6.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the final recommendation function work in this project?

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OFF

7.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the project handle the situation when a user rates a movie poorly?

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OFF

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