Stock market prediction works on linear regression to predict stock prices as predent in the dataset. Linear regression combines a specific set of input values (x) the solution to which is the predicted output for that set of input values (y). Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
The prediction of stock price is based mainly on "Opening Price", "Closing Price", "Low Price" and "High Price" of the stock given in the dataset. It predicts the stock market according to these features.
This dataset is a playground for fundamental and technical analysis. Here we have full historical daily price and volume data of Tata Global Beverages Limited in a csv file. There is a lot to learn from historical data for future prediction. We have predicted the stock market's ups and downs by using Linear Regression with good amount of accuracy.