Forecasting and Analysing Time Series Data Using Deep Learning

Rising demands in investment in cryptocurrencies are being discussed of late in recent times. The most established and well-known cryptocurrency is Bitcoin. An accurate prediction of the bitcoin price will always attract more investors. This paper aims to demonstrate the effectiveness and appropriateness of several deep learning models in time series forecasting. This experiment makes use of the CoinDesk Bitcoin Dataset. Our results demonstrate that the Gated Recurrent Unit (GRU) based model surpasses all other models in accurately predicting bitcoin prices. We experimented with different DL (Deep Learning) models, ranging from a simple model to a complicated model. Standard metrics, such as Mean Absolute Error and MSE, have been used to analyse each model. In order to make better decisions in the near future, this study will benefit the finance industry.