🚀 Movie Recommendation System using Content-Based Filtering and Hybrid Filtering to suggest movies based on user preferences. 🔹 Tech Stack Used: Python, Pandas, NumPy, Scikit-Learn 🔹 Concepts Covered: TF-IDF Vectorization, Cosine Similarity, Hybrid Recommendation 🔹 Key Features: Personalized movie suggestions, optimized performance
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🚀 Movie Recommendation System using Content-Based Filtering and Hybrid Filtering to suggest movies based on user preferences. 🔹 Tech Stack Used: Python, Pandas, NumPy, Scikit-Learn 🔹 Concepts Covered: TF-IDF Vectorization, Cosine Similarity, Hybrid Recommendation 🔹 Key Features: Personalized movie suggestions, optimized performance
varun-varada/Movie-Recommendation-System
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🚀 Movie Recommendation System using Content-Based Filtering and Hybrid Filtering to suggest movies based on user preferences. 🔹 Tech Stack Used: Python, Pandas, NumPy, Scikit-Learn 🔹 Concepts Covered: TF-IDF Vectorization, Cosine Similarity, Hybrid Recommendation 🔹 Key Features: Personalized movie suggestions, optimized performance
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