Use Case: Harnessing Your Models to Be Self-Sufficient for Better Data Insights
Dec 08, 2022
Challenges like using sources for your data that leave it unstructured and unlabeled increases the need for synthetic data, but it also creates benefits - this also allows for better training of models. Do you need more data? Do you need external or aggregate data? What about feature engineering? Some of the tech giants like Facebook and Google train their models effectively. We’ll explore how they achieved this in a real use case including everything needed to execute it yourself.