Supervised vs. Deep Learning

Squark can apply generative techniques to improve the data that goes into your AI models. Instead of creating bad art 😂, we actually create good data. Here are a couple of methods we like:

  • Enhancing missing data.  When data is missing from your columns and rows, useful values that enhance prediction can be generated.  It’s a newer approach to imputation.
  • Balancing classes.  When the classes in data are mis-balanced – such as having a few sales and many losses – synthetic data can be upsampled to create a balanced mix of data via generation and thus better models.

Want to learn more click, here (<—click. this. link. You know you want to).

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