Open
Conversation
This is the initial commit containing the project files, including:
- Python scripts for data analysis ("preprocess_data.py", "evaluate.py","fetch_data.py","recommendation_algorithm.py")
- README file with project overview and setup instructions
Created a `README.md` file to provide an overview of the project, instructions on setting up the environment, and a guide on how to run the code.
This file also includes details on project dependencies and folder structure.
Added `recommendation_algorithm.py` which contains the logic for video recommendations using collaborative filtering and content-based methods.
This module is responsible for generating video suggestions based on user preferences and engagement.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
A Video Recommendation System is a type of algorithmic solution designed to suggest videos to users based on various factors such as user preferences, historical interactions, and content features.