AI & MACHINE LEARNING PROJECT: MOVIE RECOMMENDATION ENGINE

About the program Completed a 7week 45day internship focused on designing and developing a Movie Recommendation Engine using Artificial Intelligence and Machine Learning techniques. The project aimed to build a personalized recommendation system capable of suggesting movies based on user preferences, ratings, and viewing behavior. Key responsibilities included: Data collection and preprocessing of movie datasets ratings, genres, user interactions Performing Exploratory Data Analysis EDA to understand user behavior and trends Implementing recommendation techniques such as: ContentBased Filtering Collaborative Filtering UserUser and ItemItem Matrix Factorization methods Feature engineering for improving recommendation accuracy Model evaluation using metrics like RMSE, Precision@K, Recall@K Building a simple user interfacedashboard to demonstrate recommendations Testing and optimizing model performance The final system provided personalized movie suggestions, improving user engagement and recommendation relevance. Perks Practical exposure to real-world recommendation systems Hands-on experience with machine learning algorithms Improved knowledge of data preprocessing and model evaluation techniques Experience working with Python libraries such as Pandas, NumPy, Scikit-learn Understanding of AI applications in streaming platforms Internship completion certificate Mentorship and industry-oriented project experience Who can apply? Only those candidates can apply who: are from Any and specialisation from Any are available for duration of 7 Weeks have relevant skills and interests Terms of Engagement Duration: 7 weeks (45 days) Confidentiality: Required to maintain dataset privacy and follow organizational guidelines Deliverables: Weekly progress reports and final project presentation/demo Evaluation: Based on implementation quality, innovation, and model performance Number of openings 8