We and Martha have done our research. We understand what unsupervised learning is used for, how to process data, how to cluster, how to reduce our dimensions, and how to reduce the principal components using PCA. It’s time to put all these skills to use by creating an analysis for your clients who are preparing to get into the cryptocurrency market.
Martha is a senior manager for the Advisory Services Team at Accountability Accounting, one of your most important clients. Accountability Accounting, a prominent investment bank, is interested in offering a new cryptocurrency investment portfolio for its customers. The company, however, is lost in the vast universe of cryptocurrencies. So, they’ve asked us to 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 Martha will be working with is not ideal, so it will need to be processed to fit the machine learning models. Since there is no known output for what Martha is looking for, she has decided to use unsupervised learning. To group the cryptocurrencies, Martha decided on a clustering algorithm. She’ll use data visualizations to share her findings with the board.
This Project consists of four technical analysis deliverables. You will submit the following:
- 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
The file which is used in this Analysis is: crypto_clustering.ipynb
