The aim of this project is to predict the Volume Weighted Average Price (VWAP values) in the Stock Market using various Regression techniques in Machine Learning. The past data of RELIANCE shares is taken and is used to train and test the data for prediction. Methods like Simple Linear Regression, Gradient Boosting and XGBoost is used to predict VWAP values.
Aastha2001/Stock-Market-Prediction
A Machine Learning Project which aims to predict the Volume Weighted Average Prices in the Stock Market based on the past data of Reliance company dataset. It uses the basic algorithms like Linear Regression. Also, Gradient Boosting and XGBoost techniques have been used to further increase the accuracy values. Using various Python libraries, like Pandas, Numpy, Seaborn and Matplotlib.
Jupyter Notebook