Simba Khadder

Simba Khadder

Founder & CEO at Featureform

    Simba Khadder is the founder & CEO of Featureform. He started his ML career in recommender systems where he architected a multi-modal personalization engine that powered 100s of millions of user’s experiences. He later open-sourced and built a company around their feature store. Featureform is the virtual feature store. It enables data scientists to define, manage, and serve model features using a Python framework. Simba is also a published astrophysicist, an avid surfer, and ran a marathon in basketball shoes

    All Sessions by Simba Khadder

    Day 2 04/24/2024
    1:40 pm - 2:40 pm

    Feature Stores in Practice: Build and Deploy a Model with Featureform, Redis, Databricks, and Sagemaker

    <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span>

    The term ""Feature Store"" often conjures a simplistic idea of a storage place for features. However, in reality, they serve as robust frameworks and orchestrators for defining, managing, and deploying feature pipelines. The veneer of simplicity often masks the significant operational gains organizations can achieve by integrating the right feature store into their ML platform. This session is designed to peel back the layers of ambiguity surrounding feature stores, delineating the three distinct types and their alignment within a broader ML ecosystem. Diving into a hands-on section, we will walk through the process of training and deploying an end-to-end fraud detection model utilizing Featureform, Redis, Databricks, and Sagemaker. The emphasis will be on real-world, applicable examples, moving beyond concepts and marketing talk. This session aims to do more than just explain the mechanics of feature stores. It provides a practical blueprint to efficiently harness feature stores within ML workflows, effectively bridging the chasm between theoretical understanding and actionable implementation. Participants will walk away with a solid grasp of feature stores, equipped with the knowledge to drive meaningful insights and enhancements in their real-world ML platforms and projects.

    Day 2 04/24/2024
    1:40 pm - 2:40 pm

    Feature Stores in Practice: Build and Deploy a Model with Featureform, Redis, Databricks, and Sagemaker

    <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span>

    The term ""Feature Store"" often conjures a simplistic idea of a storage place for features. However, in reality, they serve as robust frameworks and orchestrators for defining, managing, and deploying feature pipelines. The veneer of simplicity often masks the significant operational gains organizations can achieve by integrating the right feature store into their ML platform. This session is designed to peel back the layers of ambiguity surrounding feature stores, delineating the three distinct types and their alignment within a broader ML ecosystem. Diving into a hands-on section, we will walk through the process of training and deploying an end-to-end fraud detection model utilizing Featureform, Redis, Databricks, and Sagemaker. The emphasis will be on real-world, applicable examples, moving beyond concepts and marketing talk. This session aims to do more than just explain the mechanics of feature stores. It provides a practical blueprint to efficiently harness feature stores within ML workflows, effectively bridging the chasm between theoretical understanding and actionable implementation. Participants will walk away with a solid grasp of feature stores, equipped with the knowledge to drive meaningful insights and enhancements in their real-world ML platforms and projects.

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    info@odsc.com

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