##MovieRecommendation using machine learning The system will generate 10 similar movie recommendations based on cosine similarity. The movie recommendation system was trained using a dataset of movie titles. The dataset was pre-processed to remove any duplicates or irrelevant entries. The recommendation system uses the TfidfVectorizer from scikit-learn to convert movie titles into TF-IDF vectors. Cosine similarity is then calculated to measure the similarity between user input and the movie titles in the dataset.

Acknowledgments

~ The scikit-learn library for providing the TF-IDF vectorization and cosine similarity functionality. ~The contributors of the movie dataset used for training the recommendation system. ~Siddharadhan for his tutorials and educational content.