🎬 Tamil Movie Recommendation System using NLP

This project builds a content-based movie recommender system leveraging Natural Language Processing (NLP) techniques, trained on Tamil movie reviews. By using TF-IDF and cosine similarity, the model is able to recommend similar movies based on textual content.

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📂 Project Structure

• tamil_movie_reviews_train.csv: Training data with Tamil movie reviews.
• tamil_movie_reviews_test.csv: Test data to evaluate recommendations.
• processed_train_data.csv: Cleaned and processed version of the training data.
• movie.csv / with_movie_names.csv: Extended movie metadata for training/evaluation.
• tfidf_vectorizer.joblib, tfidf_matrix.joblib: Serialized vectorizer and matrix.
• train_similarity.joblib: Cosine similarity matrix.
• final_model.ipynb, workingModel.ipynb, test.ipynb: Jupyter notebooks containing the model creation, training, and evaluation steps.
• maybe.py, temp.py, workingmodel.py: Python scripts for deployment or experimentation.

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🧠 Technologies Used

• Python 3
• Pandas, NumPy
• Scikit-learn
• TF-IDF Vectorization
• Cosine Similarity
• Jupyter Notebook
• Joblib (for model serialization)

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🚀 How to Run

1. Clone this repository:

   git clone https://github.com/your-username/NLP-Movie-Recommender.git
   cd NLP-Movie-Recommender