Bay Area MLflow Meetup @ Microsoft

Join us for an evening of tech-talks about MLflow and Machine Learning from Databricks and Microsoft.

This meetup is being sponsored by Microsoft
Agenda:

6:00 - 6:30 pm: Social Hour with Food, Drinks, Beer & Wine
6:30 - 6:35 pm: Introduction & Announcements
6:35 - 7:15 pm: Talk 1: Improving the Life of Data Scientists: automating development lifecycle (Microsoft)
7:15 - 8:00 pm: Talk 2: What’s in MLflow 1.0 and Beyond ( Databricks)
8:05 - 8:30 pm: Additional Networking & Q&A

Talk 1 - Title: Improving the Life of Data Scientists: automating development lifecycle
Presenter: Avrilia Floratou and Subru Krishnan
Abstract: In this talk, we will present the basic features and functionality of Flock, an end-to-end research platform that we are developing at CISL which simplifies and automates the integration of machine learning solutions in data engines. Flock makes use of MLflow for model and experiment tracking but extends and complements it by providing automatic logging, model optimizations and support for the ONNX model format.

We will showcase Flock's features through a demo using Microsoft's Azure Data Studio and SQL Server.

Bio:
Avrilia Floratou is a Senior Scientist at Microsoft's Cloud and Information Services Lab (CISL). Her research interests broadly lie in the area of data management with a recent focus on machine learning model management. She has also been working on large-scale stream processing and is an Apache Heron committer. Before joining Microsoft, she spent 3 years at IBM Almaden Research Center working on SQL-on-Hadoop engines. She received her Ph.D. and M.Sc. in Computer Science from the University of Wisconsin-Madison and her B.S from University of Athens in Greece.

Subru Krishnan is a Principal Research Engineer at Microsoft in the Cloud and Information Services Lab (CISL) currently focusing on data science automation platforms. He has been working as a PMC on the Apache Hadoop ecosystem since 2007 with emphasis on YARN, specifically scaling it to 100K+ nodes and providing SLA guarantees. Prior to Microsoft, he worked at Yahoo! where he contributed to Oozie's precursor, near real-time stream processing on Hadoop and HBase replication.

Talk 2 - Title: What’s in MLflow 1.0 and Beyond
Presenter: Members of the MLflow Engineering Team
Abstract: MLflow 1.0 is coming soon as the first stable release of MLflow. It also packs many cleanups and improvements, such as simpler metadata management, search APIs and HDFS support. In this talk, we’ll present these new features in detail, and then discuss additional MLflow components that Databricks and other companies are working on for the rest of 2019. These new tools include a model registry to share and track models, as well as a multi-step workflow abstraction, both of which were announced at Spark + AI Summit 2019.

Bio:
Matei Zaharia is an assistant professor of computer science at Stanford University and Chief Technologist at Databricks. He started the Apache Spark project during his Ph.D. at UC Berkeley in 2009 and also worked on other open source datacenter systems, co-starting the Apache Mesos project and contributing as a committer on Apache Hadoop.

Plus, Members of MLflow Team