MLOps. Software best practices for building ML solutions
Duration
30min
Technologies
AI
Description
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.
Speaker
Fran Pérez
Software Development Engineer en Plain Concepts
I work as Machine Learning Engineer in Plain Concepts, where I can combine two of my passions: machine learning and software engineering. During last five years, I’ve developed many AI solutions using Python, R … and tons of data. In recent months, I’ve been involved in the development and optimization of Machine Learning pipelines over Databricks platforms.
Previously I was an expert in Microsoft technologies, with 15 years of experience delivering desktop and web applications.