📃: Movie Recommendation Engine Using Content-Based Filtering

[Shreya7tripathy]

Movie Recommendation Engine Using Content-Based Filtering :

Aim :
Build a Movie Recommendation Engine using Content-Based Filtering based on the IMDB top 250 movies dataset.

Dataset Information :
The dataset contains the top 250 movies from IMDB with 27 attributes like Title, Director, Genre, Plot, Ratings, etc.

Libraries :

• pandas
• nltk
• sklearn
• re

Algorithms :

• Content-Based Filtering

Brief Explanation :

• Preprocess the dataset using pandas, nltk, and re.
• Apply Content-Based Filtering to recommend movies based on attributes like genre, plot, and director.
• Use sklearn for feature extraction and model building.
• Evaluate the recommendation quality and provide visualizations of results.

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✅ To be Mentioned while taking the issue:

• Full name: Shreya Tripathy
• What is your participant role? gssoc-ext , hacktoberfest-accepted

@UTSAVS26 Can you please assign me with this task

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