Walk Through a Real World ML Production Project


Aug 23, 10:00AM PDT(05:00PM GMT). Add to Calendar: Google Yahoo
  • Free 119 Attendees
Description
Speaker

Success in productionizing ML models is difficult to achieve due to tools, processes and operational procedures. In this session, we demonstrate how data scientists and ML engineers collaborate and efficiently deploy models to production with the Wallaroo platform.

Using a real world scenario we will click down into the ML production journey that Data Scientists and ML engineers go through to take ML models into production. In this session you will learn:

  • The current pain points and blockers to production
  • The 2 persona roles in the ML production process. Data Scientist (DS) and ML Engineer
  • How the ML engineer creates a workspace in Wallaroo, and invites the DS to collaborate
  • How the DS uploads and deploys models to WL performing simple validation checks on output
  • How the ML Engineer can check model health (inference speed, etc)
  • How the DS checks logs, looks for anomalies
  • How the DS switches model in the pipeline
  • Nina Zumel

    Nina Zumel
    Nina has a Ph.D. in Robotics from Carnegie Mellon University and over 20 years of experience practicing and teaching analytics, machine learning and data science. In her roles as VP of Data Science at Wallaroo and Co-Founder & Principal Consultant for Win Vector LLC, she has led or been involved in engagements pertaining to adword revenue attribution, customer transaction models, product recommendation systems, and loan risk modeling.
    Martin BaldMartin Bald is the community lead at Wallaroo.ai. He has over two decades in the tech industry working with Microsoft. He has enjoyed roles in all areas of business from technical pre-sales, partner development, partner marketing, IT Pro evangelism, and developer communities across pro dev to student audiences. In his role with the developer community he has led many programs and projects involving meetups, webinars, workshops, hackathons, customer POCs in the IoT, AI and ML space across a variety of industries
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