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Setting up an ML Platform on GCP: Lessons Learned

Posted Dec 27
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SPEAKER
Mefta Sadat
Mefta Sadat
Mefta Sadat
Senior ML Engineer @ Loblaw Digital

Mefta Sadat is a Senior ML Engineer at Loblaw Digital. He has been here for over three years building the Data Engineering and Machine Learning platform. He focuses on productionizing ML services, tools and data pipelines. Previously Mefta worked at a Toronto based Video Streaming Company and designed and built the recommendation system for the Zoneify App from scratch. He received his MSc in Computer Science from Ryerson University focusing on research to mitigate risk in Software Engineering using ML.

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Mefta Sadat is a Senior ML Engineer at Loblaw Digital. He has been here for over three years building the Data Engineering and Machine Learning platform. He focuses on productionizing ML services, tools and data pipelines. Previously Mefta worked at a Toronto based Video Streaming Company and designed and built the recommendation system for the Zoneify App from scratch. He received his MSc in Computer Science from Ryerson University focusing on research to mitigate risk in Software Engineering using ML.

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SUMMARY

Loblaws is one of Canada’s largest grocery store chains, our team at Loblaw Digital runs several ML systems such as search, recommendations, inventory, and labor prediction on production. In this talk, Mefta shares their experience setting up their ML platform on GCP using Vertex AI and open-source tools. The goal of this platform is to help all the data science teams within their organization to take ML projects from EDA to production rapidly while ensuring end-to-end tracking of these ML pipelines. Mefta also talks about their overall platform architecture and how the MLOps tools fit into the end-to-end ML pipeline.

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