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In the ever-evolving landscape of blockchain technology, Bitcoin reigns supreme, accounting for a staggering 40% of the total crypto market cap. To capitalize on this opportunity, we embarked on a project to predict Bitcoin prices near-real time basis
In this blog post, we will show you how to unleash the full power of Databricks to process vast amounts of data, develop cutting-edge machine learning models, and make near accurate predictions for Bitcoin prices.
We implemented a 3-step approach a) market sentiment analysis, b) on-chain metrics, and 3) past price trends to unlock the true potential of Bitcoin investments.
Visualisation shows majority prevalence of neutral sentiment among market participants in last hour.
Screen capture shows Prediction based on Regression model which considers On-chain metrics and
other financial market metrics as input variables vs Actual price for 7 hours
Screen capture shows prediction of Time Series for Bitcoin model based on Prophet vs Actual price for 7 hours.
Using Databricks, we were able to quickly generate baseline models and track different machine learning versions using MLflow. This enabled us to easily compare and evaluate various models and select the most effective one. Databricks also allowed us to effortlessly manage and process vast amounts of data from multiple sources, including the Twitter API and on-chain metrics, using Delta Lake. This made it easier to develop comprehensive models that could accurately predict Bitcoin prices.
Our project highlights the importance of utilizing a comprehensive approach to predict market trends and make informed investment decisions. As the blockchain industry continues to grow, we believe that our approach could be applied to other cryptocurrencies as well.
In summary, with the vast array of powerful tools and features offered by Databricks, we were able to take our project to unprecedented heights and make accurate predictions for Bitcoin prices.