- Data Collection: Gathering data from various sources including titles, overviews, genre.
- Data Processing: Cleaning and preprocessing the data to make it suitable for analysis.
- Model Training: Using Tf-Idf vectorizer and Cosine Similarity.
To set up the project locally, follow these steps:
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Clone the repository:
git clone https://github.com/susil-123/Movie-Recommendation-using-Flask.git cd Movie-Recommendation-using-Flask
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Create virtual enviroinment:
conda create -p venv python==3.8 conda activate venv
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Install requirements:
pip install -r requirements.txt
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Run the application:
python app.py