Data versioning and data management are core components of MLOps and any end-to-end AI platform. What challenges are related to data versioning and how to overcome these. What are the benefits of using Git and data codification as a foundation of data versioning? And how open data versioning tools can enable an open MLOps ecosystem instead of closed end-to-end ML platforms. DVC and other tools: - Basic modeling scenario - Automation of modeling - Model deployments: to server or docker. DVC as a model registry. - CI/CD for ML
In this episode
Co-Founder & CEO , Iterative.ai
Dmitry is a creator of open-source tool Data Version Control - DVC.org - or Git for data. He is a former data scientist at Microsoft with Ph.D. in Computer Science. Now Dmitry is working on tools for machine learning and data versioning as a Co-Founder and CEO of Iterative.AI in San Francisco, CA.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.