Automated exploratory data analysis and model operationalization framework with a human in the loop
AWS Machine Learning
NOVEMBER 1, 2022
According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. Additionally, we won’t be able to make an informed decision post-analysis of those insights prior to building the ML models. Overview of solution.
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