Dnisde/StockPrices-TimeSeries-Prediction

we will use machine learning models to investigate the correlations and patterns behind stock closing prices and candidate data. We use the LASSO regression algorithm to extract the factors in the dataset that have a high correlation with the closing prices, and then use Support Vector Regression and Kernel ridge regression to fit and predict the closing prices of Amazon and China The closing prices of Amazon and Ping An Bank Co. The accuracy of the final prediction is over 85%.

Jupyter NotebookMIT