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AutoML suggests what columns of data to use for the model, selects and tunes the algorithm automatically, and includes the performance and reliability of the model created, along with what features influence the predictions it makes for which products are most likely to be out of stock at particular distribution centers.
That’s why it is of utmost importance to start with utilizing the right key performance indicators – there are numerous KPI examples that can make or break the quality process of data management. You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on.
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