This project aims to explore time series analysis on stocks data. It also aims to explore time series forecasting using non-deep learning (i.e., ARIMA and SARIMAX) and deep learning (i.e., Long Short Term Memory (LSTM) techniques. Various error metrics were used to asses the performance of each technique wherein LSTM had the least value across all error metrics. Thus, it was used to perform the final step which is forecasting.
Dataset Source: https://finance.yahoo.com/quote/KO