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Unified Data Analytics | Virtual Workshop - with Microsoft
Unifying Data Pipelines, Business Analytics and Machine Learning with Apache Spark™

In this virtual workshop, we’ll cover best practices for enterprises to use powerful open source technologies to 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 as it unifies data at massive scale across various sources. You’ll learn how to use ML frameworks (i.e. 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.

Learn how to build highly scalable and reliable pipelines for analytics
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


9:00 AM Databricks Keynote
9:45 AM Customer Presentation
10:15 AM Partner Presentation
10:30 AM Break
10:40 AM Data Engineering Interactive Demo & Best Practices: Preparing Data for Analytics
11:15 AM Data Science Interactive Demo & Best Practices: Model Training and Machine Learning
11:50 AM Q&A
12:00 PM Wrap Up

Sep 2, 2020 09:00 AM in Pacific Time (US and Canada)

Webinar is over, you cannot register now. If you have any questions, please contact Webinar host: Andreana Garcia-Phillips.