ML Dev Day Live Workshop

July 21, 2021, at 9 AM PT

In this live workshop, we’ll cover the best practices for enterprises to use with powerful open source technologies so you can simplify and scale your data and ML efforts. We’ll discuss how to leverage Apache Spark™ — the de facto data processing and analytics engine in enterprises today for data preparation that unifies data at a massive scale across various sources — and Delta Lake to make your data lake ML-ready. You’ll also learn how to use data and ML frameworks (TensorFlow, XGBoost, scikit-learn, etc.) to train models based on different requirements. And finally, you can learn how to use MLflow to track experiment runs between multiple users within a reproducible environment and manage the deployment of models to production on Amazon SageMaker.

  • Learn how to build highly scalable and reliable pipelines for analytics
  • Gain deeper insight into Apache Spark and Databricks, including the latest updates with Delta Lake
  • Train a model against data and learn best practices for working with ML frameworks (TensorFlow, XGBoost, scikit-learn, etc.)
  • Learn about MLflow to track experiments, share projects and deploy models in the cloud with Amazon SageMaker
  • Network and learn from your ML and Apache Spark peers

Agenda

  • 9:00–9:15 AM Welcome and Keynote From Databricks + Partner
  • 9:15–9:30 AM Customer Presentation
  • 9:30–10:50 AM Technical Hands-On Workshop
  • 10:50–11:00 AM Partner Presentation and Demo
  • 11:00–11:05 AM Prizes and Next Steps

 

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