Comet ML Office Hours: 7 Steps to a More Standardized Machine Learning Process

Join the team at Comet for a live (virtual), 8-part series exploring what it takes to create more effective, efficient, and scalable processes for your ML project work—and why you should consider adopting a more standardized approach to your ML work.

**Note: You only need to register once to have access to all 8 events!

REGISTRATION LINK: https://comet-ml.zoom.us/meeting/register/tZItf-urrzMoE9N-HWSIK68qfI1eDB_jlUeN
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Check out the scheduled events for this series below:

• January 5th: Defining Business Impact with Your Machine Learning Projects, with guest Christian Capdeville from Anaconda

• January 12th: How to Define Scope and Success Criteria for Your Machine Learning Projects

• January 19th: How to Tell if You’ve Built a Good Machine Learning Model? Use a Baseline, with guest Dr. Angelica Lo Duca

• January 26th: Understanding, Validating, Versioning, and Engineering your Data, with guests TBD

• February 2nd: How to Manage Experiments Like an Expert, with guests Santona Tuli, Susan Shu Chang, and W. Ronny Huang

• February 9th: How Experiment Management Makes it Easier to Build Better Models Faster, with guests TBD

• February 16th: How Experiment Management Makes it Easier to Build Better Models Faster, with guests TBD

• February 23rd: The Last Mile of Machine Learning and Beyond—Model Serving and Monitoring, with Comet's internal ML experts