ashishkishusrepo/movie-recommendation-system-using-machine-learning-with-python.

The goal was to build a system that can suggest personalized movie recommendations to users based on their past ratings and preferences.

Movie-Recommendation-System-using-Machine-Learning-with-Python. The goal was to build a system that can suggest personalized movie recommendations to users based on their past ratings and preferences.

Objectives:

To design and implement a movie recommendation system using collaborative filtering and content-based filtering techniques To evaluate the performance of the system using metrics such as precision, recall, and F1 score To provide personalized movie recommendations to users based on their past ratings and preferences To visualize the recommendation results using interactive dashboards and plots Methodology:

Data preprocessing and feature engineering using Python and the Pandas library Building and training a collaborative filtering model using the Surprise library Building and training a content-based filtering model using the TensorFlow library Hybrid approach combining both collaborative and content-based filtering Model evaluation and hyperparameter tuning using cross-validation and grid search Deployment of the recommendation system using a Flask API and a React frontend Expected Outcomes:

A functional movie recommendation system that provides personalized recommendations to users Evaluation metrics such as precision, recall, and F1 score to measure the performance of the system Interactive visualizations to demonstrate the recommendation results A scalable and deployable system that can handle large datasets and user traffic Deliverables:

A written report detailing the methodology, results, and conclusions A GitHub repository containing the code and documentation for the project A deployed API and frontend for users to interact with the recommendation system A presentation summarizing the key findings and results Skills Used:

Python programming language Data preprocessing and feature engineering Collaborative filtering and content-based filtering Model evaluation and hyperparameter tuning API development and deployment using Flask Frontend development using React Data visualization using Matplotlib and Seaborn