Movie Clustering : Hierarchical
- Category: Natural Language Processing
- Tools and techniques: Pandas, NumPy, NLTK, Scikit-learn, Tokenization, Lemmatization, Stop Words Removal, TF-IDF Vectorization, K-Means Clustering, Hierarchical Clustering, Affinity Propagation,Matplotlib, Seaborn, Dendrogram, Data Loading, Data Cleaning, Feature Engineering
- Project URL: https://github.com/Shubhkirti24/NLP/blob/main/ Movie_Clustering.ipynb
Project Description
In this project, we leveraged the TMDB 5000 Movie Dataset to explore and implement various unsupervised machine learning techniques for clustering movie descriptions. Our objective was to discover underlying patterns and group similar movies based on their descriptions, genres, and keywords. This project serves as an excellent demonstration of practical machine learning applications in the entertainment industry, offering insights into movie categorization and recommendation systems.