The project aims to provide retail investors with Machine Learning models to navigate through the stock market. This is achieved through the use of machine learning and Python. Several stock price prediction approaches and models are developed including Recurrent neural networks i.e. LSTM, simple linear regressions, and Decision Tree Models. By taking the past stock prices the models were trained and tested on that data to predict the stock prices.