This session delves into the innovative use of DVC (Data Version Control) and Ray for automating distributed ML pipelines, with a specific focus on Computer Vision and Generative AI applications. We will uncover how DVC's robust data and model versioning capabilities, combined with Ray's distributed computing strengths, can significantly enhance ML workflows. Participants will gain practical insights into designing, running, and managing scalable ML pipelines that not only span multiple nodes but also maintain precise version control, crucial for efficient development and deployment in cloud environments like AWS.

Mikhail Rozhkov

Affiliation: Iterative.ai

Hi, I am Mikhail Rozhkov, a seasoned Team Lead and Solutions Engineer with 7+ years of expertise in Data Science, Machine Learning, and MLOps. With a strong track record in leading teams, driving product development, and ensuring customer success, I bring the perfect blend of technical skills and a strategic mindset to help businesses harness the power of AI.

I'm interested in opportunities to contribute to cutting-edge projects and drive innovation in the fields of CV, Robotics, 3D and LLM applications.

Also, I am a co-founder of the Machine Learning REPA community of machine learning, data science, and MLOps specialists. To stay in touch, join the Machine Learning REPA community group: https://www.linkedin.com/groups/9320089/

visit the speaker at: GithubHomepage