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Registration and exhibitions

Keynote: MLOps in the Newsroom

Chris Wiggins, Chief Data Scientist, The New York Times

Using MLOps to Bring ML to Production 

David Aronchick, Head of Open Source ML Strategy, Microsoft

Netflix Presents: A Human-Friendly Approach to MLOps 

Julie Pitt, Director, Data Science Platform, Netflix

Ashish Rastogi, Content Machine Learning Lead, Netflix




Data as the Enabler of Digital Transformation 

Bill Groves, Chief Data Officer, Walmart

Real-time Financial Fraud Detection 

Arthur Garmider, Architect, Payoneer


Panel: Practical ML Challenges 

Josh Baer, Machine Learning Platform Product Lead, Spotify

Jason Evans, Director of DXP Innovation, Quadient

Michael Skarlinski, Manager of Data Science, WW 

Kishore Gagrani, Global Product Director, Dell PowerEdge 

Moderated by Asaf Somekh, Iguazio CEO


The Architecture That Powers Twitter’s Feature Store 

Brittany Wills, Software Engineer, Twitter

Serverless for ML Pipelines from A to Z 

Orit Nissan-Messing, VP of R&D, Iguazio


Deep Learning on Business Data at Uber 

Alex Sergeev, Software Engineer, Uber

The Growth and Future of Kubeflow for ML 

Maulin Patal, Product Manager, Google

Jeremy Lewi, Lead Kubeflow Engineer, Google


Stateless ML Pipelines 

James Norman, Lead Software Engineer, Nike

The RAPIDS Ecosystem – Scaling Accelerated Data Science 

Josh Patterson, GM, Data Science, NVIDIA


Best Practices for Multiplatform MLOps with Kubeflow and MLflow

Clemens Mewald, Director of Product Management, Machine Learning and Data Science, Databricks

David Aronchick, Head of Open Source Machine Learning Strategy, Microsoft

Thea Lamkin, Open Source Program Manager, Google

Moderated by Yaron Haviv, CTO, Iguazio


MLOps Challenges and Future 

Yaron Haviv, CTO, Iguazio



MLOps Rooftop Drinks

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