/Cryptocurrencies

Unsupervised machine learning models used to group the cryptocurrencies to help prepare for a new investment.

Primary LanguageJupyter Notebook

Cryptocurrencies

Purpose

Create a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment.

The data needs to be processed to fit the machine learning models. Since there is no known output, unsupervised learning needs to be used. To group the cryptocurrencies, a clustering algorithm is used. Data visualizations are used to share findings.

Preprocessing

Encoding

Principal Component Analysis

Explained Variance Ratio

The three principal components explain about 6.983% of the variance in this dataset.

Elbow Curve

K-Means Model

Concatenate Dataframe

Visualizations

3D Scatter Plot of PCA Data and 4 Clusters from clustered_df

Hvplot Scatter Plot Using x="TotalCoinsMined" and y="TotalCoinSupply".

Hvplot Table with Tradable Currencies