Natesh Arunachalam

How to Build Robust Machine Learning Models

The adoption of AI offers numerous potential benefits. However, it has also become increasingly common for AI models to pose their own unique set of risks. I will be presenting a robust pipeline for machine learning model development that spans from data to deployment. Adoption of this pipeline can help mitigate some of the common risks posed by ML models.

Natesh is a Lead Data Scientist at Finicity where he creates Machine Learning products leveraging open banking data. Prior to this, he was a core member of the Machine Learning CoE at JPMChase and specialized in lending, fraud and marketing models.

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