Machine Learning and Artificial Intelligence based money exchanging have pulled in enthusiasm in the recent years with the introduction of Bitcoins. The cost of Bitcoins has increased in a large scale and it is fairly difficult to predict the future cost per Bitcoin. In this study, we utilize a machine learning and deep learning model to analyze the digital currency market to predict the cost of Bitcoin per day. We dissect everyday information for 1,691 cryptographic forms of money for the period between November 2017 and April 2019. The study shows that straightforward exchanging procedures assisted by best in class AI algorithms have met the standard benchmarks. Our outcomes also show that non-inconsequential, basic algorithmic instruments can help in envision of momentary development of the cryptographic money. The proposed system uses a Bi- directional LSTM for forecasting the bitcoin prices. The proposed model was able to trace the test dataset with Mean Absolute Percentage Error of 13%. The model is helpful for the user to take decision on investing in Bitcoins.
