Tabular data is everywhere in the corporate world. I feel like there is a zillion opportunities to make money with these transformers. But how to enter that market remains a mystery to me.
I think any enterprise data science use-case where the original data is stored in some relational form. E.g. recommendations, churn prediction, fraud, etc.
Tabular data is everywhere in the corporate world. I feel like there is a zillion opportunities to make money with these transformers. But how to enter that market remains a mystery to me.
Is this "data is oil" or something else?
> applications like customer analytics, fraud detection, and supply chain optimization
Part of a graph rewrite engine? Of an optimizing compiler? Complex Event Processing?
Exciting to see end-to-end deep learning go head-to-head with XGBoost and random forest.
Why would I need to use this over a flexible multi-agent framework? What’s the benefit?
Can someone explain the use case for this
I think any enterprise data science use-case where the original data is stored in some relational form. E.g. recommendations, churn prediction, fraud, etc.