
MLOps. Software best practives for building ML solutions
In this session we will talk about MLOPs, which is based on DevOps principles and practices to increase the effectiveness of workflows in Machine Learning projects.
Schedule
- Achieve faster model development and experimentation.
- Achieve faster deployment of production models.
- Quality control.
- Continuous integration and delivery through Azure DevOps.
- Azure Databricks.
- MLFlow – Machine Learning Lifecycle Platform.
Finally, we will spend the last few minutes answering any questions that may arise during the session.
Speakers

Fran Pérez
Software Development Engineer en Plain Concepts
Previously I was an expert in Microsoft technologies, with 15 years of experience delivering desktop and web applications.

Kevin Albes
Software Development Engineer en Plain Concepts
Currently I also play the role of Delivery Lead, helping my team with the methodology and communication with the client.