For this project, I developed a machine learning model that forecasts financial metrics for a business based on multivariate time series data. My model took into account various factors such as revenue, expenses, cash inflows and outflows, and other financial indicators, and used them to generate accurate predictions for the next several months. To improve the accuracy of my model, I also included cash flow simulations that adjust the forecasting based on changes in incoming and outgoing cash flows. I deployed the model on AWS using a Flask API on Amazon Elastic Beanstalk, which allowed for easy scalability and accessibility. This project demonstrates my expertise in financial forecasting, time series analysis, and full stack development, and shows how these skills can be applied to real-world business problems. By deploying the model on AWS, I also showcase my proficiency in cloud computing and web application deployment.