This project is a starting point for unsupervised machine learning. Specifically utilizing skills in data processing, clustering, reducing dimensions, and reducing principal components. The final result is a clean dataset with 532 tradeable cryptocurrencies visualized with tables, scatterplots and 3D scatterplots. All analysis is written in Python.

• Source Code: Crypto Currency
• Source Data: CryptoCompare
• Technology: scikit-learn, hvPlot

• Deliverable 1: Preprocessing the Data for PCA
• Deliverable 2: Reducing Data Dimensions Using PCA
• Deliverable 3: Clustering Cryptocurrencies Using K-means
• Deliverable 4: Visualizing Cryptocurrencies Results