On-Demand Webinar

Feature Engineering with KubeFlow Feast

Define, Manage and Validate Models with Ease

MLOps holds the potential to change the way we understand and use the data in an organization. It focuses on scalability and greater collaboration for machine learning models to be production and deployment ready. Along the way, there may be many challenges, especially during the training and inference process.

Let the experts guide you on how to manage, define, discover, validate, and serve features to models at the time of training and inference using KubeFlow Feast. Also, learn about how to detect frauds and rank drivers, and more.

In this webinar, join us to gain insight on:
  • MLOps Overview
  • KubeFlow Overview
  • MLOps Pipeline
  • What is Feature Engineering
  • What is Feast
  • Fraud Detection example with KubeFlow Feast
  • Driver Ranking example with KubeFlow Feast
Feature Engineering with KubeFlow Feast

Ashir Zahidi

MLOps Engineer at Royal Cyber

Hassan Sherwani

Data Scientist Architect at Royal Cyber

Watch On-Demand