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Machine Learning Office Hours: Seven Steps for Standardizing ML Projects
Join us for a weekly gathering of data scientists and machine learners—both aspiring and professional—who want to talk shop and create community with one another. Harpreet Sahota, Data Scientist at Comet and host of The Artists of Data Science podcast, will guide these thoughtful conversations.

Each Wednesday, from January 5 - February 23rd, 2022, we'll explore what it takes to establish more effective, repeatable, and scalable processes for your machine learning projects.

If you have questions in advance of each event, you can submit those via this Google Form:

Below is a look at what each session will cover:

* 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 Matt Blasa, Jimmy Whitaker from Pachyderm, and Dr. Abe Gong from Great Expectations

* 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


This event series is sponsored by Comet, an ML development platform that enables practitioners and teams to track, compare, explain, optimize, and monitor their experiments and models.
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