This is a content-based movie recommender system, trained on a dataset of 5,000 films. The system utilizes cosine similarity to recommend movies based on user preferences, offering personalized suggestions. This project includes a fully functional GUI web application, data processing, and deploying user-friendly solutions.

Library used : Numpy, Pandas, Sk-Learn, NLTK, Streamlit.

This is a brain tumor detection model ,leveraging both deep learning and machine learning techniques. Utilizing Convolutional Neural Networks (CNN), I performed extensive Exploratory Data Analysis (EDA) and applied strategies to reduce overfitting, resulting in a highly accurate and robust model. My work showcases my ability to combine advanced algorithms with data-driven insights to solve complex medical challenges.

Library used : Numpy, Pandas, Matplotlib, Seaborn, Sk-Learn.

This time series forecasting model is designed to predict future trends based on historical data. The model leverages algorithms for accurate forecasting, with a focus on performance optimization. This project highlights my proficiency in time series analysis, data modeling, and deploying predictive solutions.