• Led comprehensive data science and analytics research to identify key health indicators for diabetes and develop a predictive model with the best accuracy.• Transformed the predictive model into a web application using React for the front end and Flask for the back end, which predicts if the patient is prone to diabetes. If not, it provides the percentage risk and also highlights the contributing factor to help people stay safe.• Technologies used: Python, React, Flask, HTML, CSS, JavaScript, Scikit-Learn, Pandas, NumPy, Matplotlib, Joblib.

• Utilized data science and data analytics to build a model for sleep efficiency.• Developed a comprehensive research paper titled ”Comparative Analysis of Machine Learning Methods for Enhancing Sleep Efficiency and Prediction”.• Collaborated with senior researchers to enhance the accuracy and performance of the predictive model.• Technologies used: Python, Scikit-Learn, Pandas, NumPy, Matplotlib.