Every agency today wants to accelerate innovation by building AI into their practice. However, most agencies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.
In this
workshop, you will learn how to leverage Apache Spark™, use ML frameworks like Tensorflow, XGBoost, Scikit-Learn, and utilize MLflow to track experiment runs between multiple users within a reproducible environment.
By
registering for this complimentary half-day workshop you will have the opportunity to:
- Learn how to build highly scalable and reliable pipelines for analytics
- Gain a deeper insight into Apache Spark and Azure Databricks, including the latest updates with Delta Lake
- Train a model against data and learn best practices for working with ML frameworks (i.e. - XGBoost, Scikit-Learn, etc.)
- Learn about MLflow to track experiments, share projects and deploy models in the cloud and on-prem
- Network and learn from your ML and Apache Spark peers
If you have any questions, please
contact me directly. See you at the workshop!
