Feature Store as a Data Foundation for Machine Learning

Learn how to build a centralized, scalable Feature Store for Machine Learning, to drive innovation at scale

On-Demand Webinar

Feature Store is a key component of the ML stack and data infrastructure. By enabling robust feature engineering and management, it helps organizations save massive amounts of resources, innovate faster, and drive ML processes at scale. Request the webinar and learn how to build a scalable Feature Store with a data mesh pattern; see how to achieve consistency between real-time and training features, to improve reproducibility with time-traveling for data.

You will learn about:

Modern Data Lakes and Modern ML Infrastructure
Existing and Emerging Architectural Shifts
Feature Store: Overview and Reference Architecture
AWS Perspective on Feature Store
Provectus ML Infrastructure Acceleration Program

Speakers:

Stepan Pushkarev, Chief Technology Officer, Provectus
Gandhi Raketla, Senior Solutions Architect, AWS
German Osin, Senior Solutions Architect, Provectus

Who should attend:

Technology executives & decision makers
Manager-level tech roles
Data architects & analysts
Data engineers & Data scientists
ML practitioners & ML engineers
Developers

Let’s explore major use cases and ways to build a centralized, scalable Feature Store for Machine Learning!

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On-Demand Webinar

Feature Store is a key component of the ML stack and data infrastructure. By enabling robust feature engineering and management, it helps organizations save massive amounts of resources, innovate faster, and drive ML processes at scale. Request the webinar and learn how to build a scalable Feature Store with a data mesh pattern; see how to achieve consistency between real-time and training features, to improve reproducibility with time-traveling for data.

You will learn about:

Modern Data Lakes and Modern ML Infrastructure
Existing and Emerging Architectural Shifts
Feature Store: Overview and Reference Architecture
AWS Perspective on Feature Store
Provectus ML Infrastructure Acceleration Program

Speakers:

Stepan Pushkarev, Chief Technology Officer, Provectus
Gandhi Raketla, Senior Solutions Architect, AWS
German Osin, Senior Solutions Architect, Provectus

Who should attend:

Technology executives & decision makers
Manager-level tech roles
Data architects & analysts
Data engineers & Data scientists
ML practitioners & ML engineers
Developers

Let’s explore major use cases and ways to build a centralized, scalable Feature Store for Machine Learning!