In recent years,Bitcoin ecosystem has gained the attention of consumers, businesses, investors and speculators alike.As a result of blockchain-networkbased feature engineering ,macro-economic factors of actual market and machine learning algorithms optimization, we can obtain up-down Bitcoin price movement classification accuracy of roughly 55 percent. This research is concerned with predicting the price of Bitcoin using machine learning. The goal is to ascertain with what accuracy can the direction of Bitcoin price in USD can be predicted. The price data is sourced from the Bitcoin Price Index . The task is achieved with varying degrees of success through the implementation of a Bayesian optimised recurrent neural network (RNN) and Long Short Term Memory (LSTM) network.