Map the Stock Market with Self Organizing Maps (SOMs)
mar. 25 septembre à 00:00
Self-organizing maps are an unsupervised learning approach for visualizing multi-dimensional data in a two-dimensional plane. They are great for clustering and finding out correlations in the data. In this workshop we will apply self-organizing maps on historical US stock market data to find out interesting correlations and clusters. You should have a working knowledge of Python and machine learning, not for beginners. Bring your laptop.
Nous avons temporairement désactivé la possibilité de naviguer vers les tags.