MLOps Summit schedule

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REGISTRATION & LIGHT BREAKFAST

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WELCOME NOTE & OPENING REMARKS

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Setting up MLOps In An FMCG To Realise The Value of AI

ML DESIGN & DEVELOPMENT

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Tom Ewing

Tom Ewing - Principal Machine Learning Engineer - Saint-Gobain

Machine Learning Engineering: From Prototype to Production

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ML Performance in the Real World: What They Don’t Teach You in School

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COFFEE & NETWORKING BREAK

ML FRAMEWORKS & INFRASTRUCTURE

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Pavlos Mitsoulis-Ntompos

Pavlos Mitsoulis-Ntompos - MLOps Engineering Manager - King

APIs: They Matter More Than You Think in Machine Learning

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Natalia Koupanou

Natalia Koupanou - Senior Lead Data Scientist - Tide

Open Source Software - A Better Solution?

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Key ideas for Optimizing ML Training Pipeline and Model Accuracy

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Andy McMahon

Andy McMahon - Machine Learning Engineering Lead - NatWest Group

Building End-to-end Frameworks for AI

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LUNCH

MODEL TRAINING & MANAGEMENT

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Building ML Ops Platform - Challenges and Considerations

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Chris Sarakasidis

Chris Sarakasidis - Lead Machine Learning Engineer - MLOps - ITV

Modern MLOps: Simplifying and Automating ML Pipelines Using Databricks and Kubernetes In AWS

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Creating Reproduceable ML Pipelines & Environments

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COFFEE & NETWORKING BREAK

TOOLS & TECHNIQUES

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Demystifying the MLOps Infrastructure Stack

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Embedding Trusted AI Within Your Models

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PANEL: From Concept to Production - The Best Opportunities to Utilise MLOps

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NETWORKING RECEPTION

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END OF DAY 1

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DOORS OPEN & LIGHT BREAKFAST

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WELOME NOTE

AUTOML

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Automating ML Workflows: How Can You Benefit?

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Making AI Work For You

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Ghida Ibrahim

Ghida Ibrahim - Lead Quantitative Engineer - Meta

An Intro To AIOps: How To Scale IT Operations With AI

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COFFEE & NETWORKING BREAK

SCALING & MANAGEMENT

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Harpal Sahota

Harpal Sahota - Lead Data Scientist - MATCHESFASHION

The Journey of MLOps At MATCHESFASHION

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There Is No Such Thing As MLOps

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Model Management, Deployment, Lineage & Monitoring

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Deploy & Accelerate Optimisations to Improve Your Business Outcomes

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LUNCH

PRACTICAL MLOPS

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Advanced ML Methods For Automating Image Labeling

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A Framework For Understanding, Exploration and Forecasting

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PANEL: The ROI of MLOps: Do the Pros Outweigh the Cons?

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END OF SUMMIT

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