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AGENDA

MAIN TRACK

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 8:00-9:00    
Registration and exhibitions

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 9:00-9:30    
Keynote: MLOps in the Newsroom

Chris Wiggins, Chief Data Scientist, The New York Times

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 9:30-10:00    
Using MLOps to Bring ML to Production 

David Aronchick, Head of Open Source ML Strategy, Microsoft

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 10:00-10:30    
Netflix Presents: A Human-Friendly Approach to MLOps 

Julie Pitt, Director, Data Science Platform, Netflix

Ashish Rastogi, Content Machine Learning Lead, Netflix

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 10:30-10:50   

Break

 

 10:50-11:20    
Data as the Enabler of Digital Transformation 

Bill Groves, Chief Data Officer, Walmart

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 11:20-11:50    
Real-time Financial Fraud Detection 

Arthur Garmider, Architect, Payoneer

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 11:50-12:35    

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

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 12:35-1:35pm   
Lunch

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 1:35-2:05pm    
The Architecture That Powers Twitter’s Feature Store 

Brittany Wills, Software Engineer, Twitter

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 2:05-2:35pm    
Serverless for ML Pipelines from A to Z 

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

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 2:35-3:05pm    

Deep Learning on Business Data at Uber 

Alex Sergeev, Software Engineer, Uber

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 3:05-3:35pm    
The Growth and Future of Kubeflow for ML 

Maulin Patal, Product Manager, Google

Jeremy Lewi, Lead Kubeflow Engineer, Google

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 3:35-3:55pm   
Break

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 3:55-4:25pm    
Stateless ML Pipelines 

James Norman, Lead Software Engineer, Nike

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 4:25-4:55pm    
The RAPIDS Ecosystem – Scaling Accelerated Data Science 

Josh Patterson, GM, Data Science, NVIDIA

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 4:55-5:40pm    

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

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5:40-6:00pm    

MLOps Challenges and Future 

Yaron Haviv, CTO, Iguazio

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 6:00-7:00pm    
Exhibition

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 6:00-8:00pm    

MLOps Rooftop Drinks

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TRAINING

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 8:00-9:00    

Registration and exhibitions

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 9:00-10:30    
Building an End-to-End Machine Learning Pipeline with Kubeflow 

Karl Weinmeister, Developer Advocacy Manager, Google

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 10:30-10:50   
Break

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 10:50-11:35    

Deploying Serverless ML pipelines with MLRun, Nuclio and Kubeflow 

Or Zilberman, Data Scientist, Iguazio

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 11:35-12:35pm    

Accelerating Machine Learning with MLflow 

Ben Wilson, Senior Resident Solutions Architect, Databricks

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 12:35-1:35   

Lunch

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 1:35-2:05pm    
Running Spark on Kubernetes 

Marcelo Litovsky, Solutions Architect, Iguazio

Adi Hirschtein, VP of Product, Iguazio

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 2:05-2:50pm    

Spotify's Machine Learning Workflow

Ryan Clough, Senior Machine Learning Engineer, Spotify

Gandalf Hernandez, Machine Learning Platform Engineering Manager, Spotify

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2:50-3:35pm    
Introducing KFServing: Serverless Model Serving Across ML Frameworks 

Dan Sun, Senior Software Developer, Bloomberg

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 3:35-3:55pm   
Break

 

 3:55-4:25pm    
Kubeflow 0.6 Release Update 

Josh Bottum, VP, Arrikto

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 4:25-4:55pm    

Quick and Efficient Chat Bots 

Steven Jones, Lead Architect Messaging and AI, IBM

Jenny Mallette, Cognitive Software Engineer, IBM

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 4:55-5:25pm    

Machine Learning with SageMaker 

Mark Roy, Machine Learning Specialist, AWS

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 5:25-6:00pm    

Using Progressive Delivery with Kubernetes 

Paul Curtis, Principal Solutions Architect, Weaveworks

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