DevOps for Data Science

Successful ML deployments require DevOps changes within your IT department

We know the challenges organizations face when trying to operationalize AI and deploy machine learning models into production. In this webinar, join Anaconda’s IT experts David Mason and Bryan Tucker to learn best practices for deploying AI/ML at scale—without having to become an expert in containers, DevOps, or Kubernetes.

In this webinar, you will learn: 
  • the challenges of deploying machine learning models into production 
  • how the right tools can serve as DevOps for delivering AI at scale
  • how to automate and optimize the deployment process

Meet Our Speakers

  • David Mason
    Anaconda Director of IT

    David leads Anaconda’s IT team, which manages the technology resources at the core of our operations. He comes to Anaconda with 16 years’ experience in information technology operations. He has worked at nonprofits, startups, and insurance and financial services companies, giving him exposure to a wide range of technologies and solutions.

    David holds a BA from the University of Texas at Austin and maintains GCIH and GSEC certifications. He is a member of the GIAC Advisory Board.
  • Bryan Tucker
    Systems Engineer

    Bryan Tucker plays a pivotal role on Anaconda’s IT team as a Systems Engineer. With over 10 years of IT experience, specific to systems and infrastructure, he keeps the Anaconda machine going. He has experience running rapidly expanding infrastructures in tech, healthcare, and data science industries. 

    Bryan has a BBA in Computer Information Systems from Texas State University.
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