A movie recommender system using the IMDB 5000 Movies dataset. It calculates cosine similarity between movie descriptions after preprocessing text data with stemming, tokenization, and TF-IDF vectorization. Built with Python, Pandas, Scikit-learn, and NLTK for movie recommendations.
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A movie recommender system using the IMDB 5000 Movies dataset. It calculates cosine similarity between movie descriptions after preprocessing text data with stemming, tokenization, and TF-IDF vectorization. Built with Python, Pandas, Scikit-learn, and NLTK for movie recommendations.
maafaq80/Recommender_System_Using_Cosine_Similarity
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A movie recommender system using the IMDB 5000 Movies dataset. It calculates cosine similarity between movie descriptions after preprocessing text data with stemming, tokenization, and TF-IDF vectorization. Built with Python, Pandas, Scikit-learn, and NLTK for movie recommendations.
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