This project was carried out as the final assignment for the Mathematical Optimization for Data Science course. The goal of the analysis was to compare two variants of the Frank-Wolfe Method with the Projected Gradient Method on the Markowitz portfolio optimization problem.

This is the repository of Machine Learning Internship I have done with CareerLauncher endorsed by AICTE and Intel Partnership

This is a project which uses Data Science, Machine learning to predict the stock movements, minimize the risk and maximise gains of portfolio using fama-french factors and many other models.Also the sentiment towards stocks are also monitored using sentiment analysis. Garch Model is used to predict the volatility and movements for intraday trading.