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Visualization & Classification of a 13 dimensional wine data using an unsupervised learning technique called Self Organizing Maps. We map a 13D data into a 2D grid and used color profile to differentiate data belonging to each class.
Identify major customer segments on a transnational data set that contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.
Combined financial Python programming skills with the new unsupervised learning skills that I acquired. You’ll create a Jupyter notebook that clusters cryptocurrencies by their performance in different time periods. Plotted the results so I can visually show the performance to the board.