Am a big proponent of exploratory data analysis, and making it initially as simple, visual and goal oriented as possible. Here a piece from KDNuggets that shows one approach. Link through. Have read KDN for years, long before AI became big and we did what was called optimization and analytics.
EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code... and it might even be fun! KNIME Fall Data Talks Bringing Business and Data Science Together
By Francois Bertrand, coder & designer for data visualization and games.
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