Week 1

All Times US Pacific Standard Time (PST)

Tuesday, Jan 19

09:00 AM
Keynote Interview: Solmaz Shahalizadeh
10:00 AM
How Spotify Does ML At Scale
10:40 AM
MLOps for High-Stakes Environments
11:10 AM
How Feature Stores Enable Operational ML
11:40 AM
Data Prep Ops: The Missing Piece of the MLOps Puzzle
12:10 PM
TWIMLconnect (Networking)
01:00 PM
End-to-End ML with Cloudera Machine Learning

Wednesday, Jan 20

09:00 AM
Keynote Interview: Faisal Siddiqi
10:00 AM
When Good Models Go Bad: The damage caused by wayward models and how to prevent it
10:40 AM
Build, Buy and the Golden Ratio: How Theator scaled up its continuous training framework
11:10 AM
Machine Learning is Going Real-Time
11:40 AM
Unified MLOps: Feature Stores & Model Deployment
12:10 PM
Team Teardown: Driving Platform Adoption and Success at Spotify
01:00 PM
One Flow to Rule Them All: Building the end to end ML project to production in Dataiku DSS

Thursday, Jan 21

09:00 AM
Deploying a Fraud Detection Model with a Feature Store
12:00 PM
TWIMLconnect (Networking)
01:00 PM
Algorithmia in Action: Take your ML models from training to production

Friday, Jan 22 (Exec Summit)

09:00 AM
Executive Summit Keynote: How to Ensure ML Project Success
09:45 AM
Building the Business Case for ML Platforms
10:20 AM
Why ML Projects Fail and How to Ensure Their Success
10:55 AM
Building Teams and Culture that Support ML Innovation
11:30 AM
Executive Summit Roundtable Discussion

Week 2

All Times US Pacific Standard Time (PST)

Tuesday, Jan 26

09:00 AM
Keynote Interview: Chris Albon
10:00 AM
Building ML Platform Capabilities at Global Scale
10:40 AM
AI Operationalization: Where the AI Rubber Hits the Road for the Enterprise
11:10 AM
Coming Soon!
11:40 AM
Top Trends in Enterprise Machine Learning for 2021
12:10 PM
Team Teardown: MLOps in the Cloud for IoT at iRobot
01:00 PM
ClearML: Your R&D on MLOps! From zero to hero in two lines of code

Wednesday, Jan 27

09:00 AM
Keynote Interview: Ya Xu
10:00 AM
Cost Transparency and Model ROI
10:40 AM
Making Models Work: How an optimized ML lifecycle can drive better ROI
11:10 AM
ML Product Experiments at Scale
11:40 AM
Build an End-to-End ML Workflow for Your Organization
12:10 PM
Operationalizing Responsible AI
01:00 PM
Explainable Monitoring for Successful AI Deployments

Thursday, Jan 28

09:00 AM
Hands-On Feature Store and Model Deployment with Splice Machine
12:00 PM
Block
01:00 PM
Using Unity to Generate Synthetic data and Accelerate Computer Vision Training

Friday, Jan 29 (Unconference)

09:30 AM
Unconference
Scroll to Top