The purpose of this analysis was to identify which cryptocurrencies are available for trading on the market and to group them in a classification system to help make the best investment possible. An unsupervised machine learning model is how I conducted this analysis since there was a significant amount of data that needed to be analyzed and the output is unknown. I ultimately used a clustering algorithim to help classify each crypto currency. Overall, there are 532 tradeable cryptocurrencies that can be grouped into 3 different clusters.
