The purpose of this project is to provide an analysis to clients who are preparing to get into the cryptocurrency market by using unsupervised machine learning to analyze a database of cryptocurrencies and create a report including the traded cryptocurrencies classified by group according to their features.
The following methods are used for the analysis: 1. Preprocess the Data for PCA 2. Reduce Data Dimensions Using PCA 3. Cluster Cryptocurrencies Using PCA 4. Visualize Cryptocurrency Results
Data Source: crypto_data.csv
Software:
- Python 3.7
- Anaconda Navigator (anaconda3)
- Jupyter Notebook