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Models to Production in Two Weeks

Models to Production in Two Weeks
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AI Sweden's Office - Fleminggatan 41
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April 4, 2023
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9:00 am
-
1:00 pm
CET

Introducing the Feature Store, MLOps, and the FTI framework

Is it taking too long to go from a model in a notebook to a model that is adding to the bottom line of your business? MLOps and the FTI pattern for architecting machine learning (ML) systems are quickly becoming the de facto way to build production ML systems with a Feature Store. Join us to learn how to architect your ML systems as Feature pipelines, Training pipelines, and Inference pipelines (FTI Pipelines) that are connected together via a Feature Store and managed by best practices from MLOps. We will present examples of FTI Pipelines from industry for both batch ML systems and online ML systems in the context of the Hopsworks platform. 

Learn about best practices for feature engineering, model training, and batch/online inference in Python, Spark, and SQL, and learn about how a Feature Store can accelerate your time to value for ML.

The space has limited seating so please RSVP until March 31st.

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Agenda:

09:00 AM - 09:30 AM: Registration & Coffee

09:30 AM - 10:40 AM: Introduction & Principles for putting ML in Production

  - Developing and architecting ML Systems for Production from Day 1

  - FTI pipelines, MLOps Principles, and the Feature Store

10:40 AM - 11:00 AM: Coffee and Fika

11:00 AM - 12:00 PM: Sharing Practical Experience from building ML Systems

  - How to Build Batch ML Systems

   - How to Build  Real-Time ML Systems

12:00 PM - 13:00 PM: Lunch Networking opportunity with your peers and Hopsworks experts

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Thank you for registering!
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Models to Production in Two Weeks

calendar icon
April 4, 2023
clock icon
9:00 am
CET
clock icon
AI Sweden's Office - Fleminggatan 41

Learn about best practices for feature engineering, model training, and batch/online inference in Python, Spark, and SQL, and learn about how a Feature Store can accelerate your time to value for ML.

Is it taking too long to go from a model in a notebook to a model that is adding to the bottom line of your business? MLOps and the FTI pattern for architecting machine learning (ML) systems are quickly becoming the de facto way to build production ML systems with a Feature Store. Join us to learn how to architect your ML systems as Feature pipelines, Training pipelines, and Inference pipelines (FTI Pipelines) that are connected together via a Feature Store and managed by best practices from MLOps. We will present examples of FTI Pipelines from industry for both batch ML systems and online ML systems in the context of the Hopsworks platform. 

Learn about best practices for feature engineering, model training, and batch/online inference in Python, Spark, and SQL, and learn about how a Feature Store can accelerate your time to value for ML.

The space has limited seating so please RSVP until March 31st.

-------

Agenda:

09:00 AM - 09:30 AM: Registration & Coffee

09:30 AM - 10:40 AM: Introduction & Principles for putting ML in Production

  - Developing and architecting ML Systems for Production from Day 1

  - FTI pipelines, MLOps Principles, and the Feature Store

10:40 AM - 11:00 AM: Coffee and Fika

11:00 AM - 12:00 PM: Sharing Practical Experience from building ML Systems

  - How to Build Batch ML Systems

   - How to Build  Real-Time ML Systems

12:00 PM - 13:00 PM: Lunch Networking opportunity with your peers and Hopsworks experts

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Thank you for registering!
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Feature Store

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