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redhat-et / customer-growth-model

The repo enables accurate customer revenue forecasting using ARIMA and other time series methods. It provides practical examples, data preprocessing, evaluation, and optimization. It also identifies potential customers through market analysis and predictive modeling. Empowering businesses for data-driven growth.
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Updating notebooks #14

Closed suppathak closed 6 months ago

suppathak commented 6 months ago
review-notebook-app[bot] commented 6 months ago

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suppathak commented 6 months ago
review-notebook-app[bot] commented 6 months ago

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hemajv commented on 2024-03-11T21:32:03Z ----------------------------------------------------------------

Since we have many accounts, to keep the notebook concise I think we should just plot around 5 accounts and pick 1-2 each for low, medium, high categories


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hemajv commented on 2024-03-11T21:32:03Z ----------------------------------------------------------------

I think we should also include a brief description of what MLFlow is and what its used for along with a link to https://mlflow.org/

also, rephrase to...we will be logging the MAPE values to MLFlow. You can omit the different runs


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hemajv commented on 2024-03-11T21:32:04Z ----------------------------------------------------------------

maybe just a quick mention before this cell stating that we have an MLFlow deployment which we are using here


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