Tuesday, December 4 - Hyatt Regency San Francisco

Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with managing and preparing large datasets for analytics; complexity of managing an explosion of ML frameworks and moving models in development to production.

Microsoft and Databricks invite you to this workshop where we we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll demonstrate 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 various ML frameworks - Tensorflow, XGBoost, Scikit-Learn and others 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. 

Join this ½ day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. This free workshop will give you the opportunity to:

  • Learn to build highly scalable and reliable pipelines for analytics
  • Deeper insight into Apache Spark and Databricks
  • Best practices for working with various ML frameworks - Tensorflow, XGBoost, Scikit-Learn, etc.
  • Leverage MLflow to track experiments, share projects and deploy models in cloud and on-prem
  • Network and learn from your ML and Apache Spark peers

We are also excited to announce Yogesh Natarajan, Sr. Software Engineer, from Adobe as our customer speaker!

AGENDA AT A GLANCE

8:30-9:00 Registration, Breakfast & Networking
9:00-9:45 Opening Remarks - Unifying Data Science and Data Engineering
9:45-10:15 The Power of Azure Databricks at Adobe
10:15-10:45 Networking with Peers
10:45-11:30 Interactive Demo & Best Practices on Preparing Data for Analytics and Machine Learning using Databricks Runtime for ML
11:30-12:15 Interactive Demo & Best Practices on Distributed Deep Learning and MLflow
12:15-12:30 Q&A

Space is limited for this event. Sign up today to reserve your spot!

Please fill out the form to confirm your spot