MLOps Workshop: The Full ML Lifecycle - How to Use ML in Production
Details
Hello, Big Data enthusiasts!
We're excited to announce our first post-Covid event, which will be on the subject of MLOps! Data consultants from D ONE will walk us through the full Machine Learning lifecycle. This will be a 3-hour hands-on event which requires that you bring your own laptop (or team-up with an another attendee on the spot). Food, drinks, and venue are kindly sponsored by D ONE.
Description:
MLOps is a Machine Learning (ML) engineering culture and practice that aims to unify ML system development (Dev) and ML system operation (Ops). It serves as a counterpart to the DevOps practice in classical software development which involves Continuous Integration (CI) and Continuous Deployment (CD). Practicing MLOps advocates automation and monitoring at all steps of ML system construction, including integration, testing, releasing, deployment and infrastructure management.
In this workshop, we discuss how the continuous delivery principles from software engineering translate to data science and machine learning by introducing all steps of an MLOps workflow. In the subsequent practical part, we use real data from wind turbine parks and develop an end-to-end solution from data versioning to model training to model deployment. We will focus on state-of-the-art open-source tools such as Data Version Control (DVC), MLflow and Apache Airflow.
This workshop will provide data professionals with the essential tools and knowledge to create, integrate, continuously train and deploy ML systems in production environments using open-source tools that can be used in any cloud setting.
Speakers:
Technologies:
Sponsor:
D ONE is a Swiss consultancy for data driven value creation. Hands-on business practitioners with academic excellence provide corporate transformation towards information enterprise. Our clients recommend us because we make success happen in an easy-to-do-business-with way.
Agenda:
- 10:00 - Welcome
- 10:15 - Workshop, Part 1
- 11:30 - Coffee Break
- 11:45 - Workshop, Part 2
- 13:00 - Food, Drinks, Networking
Notes:
COVID-19 safety measures
MLOps Workshop: The Full ML Lifecycle - How to Use ML in Production