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The Sequence Pulse: The Architecture Powering Data Drift Detection at Uber

TheSequence

Like any large tech company, data is the backbone of the Uber platform. Not surprisingly, data quality and drifting is incredibly important. Many data drift error translates into poor performance of ML models which are not detected until the models have ran.

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Building ML Platform in Retail and eCommerce

The MLOps Blog

The ML platform can utilize historic customer engagement data, also called “clickstream data”, and transform it into features essential for the success of the search platform. We can collect and use user-product historical interaction data to train recommendation system algorithms.

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LLMOps: What It Is, Why It Matters, and How to Implement It

The MLOps Blog

Tools range from data platforms to vector databases, embedding providers, fine-tuning platforms, prompt engineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. Monitoring Monitor model performance for data drift and model degradation, often using automated monitoring tools.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. As you’ve been running the ML data platform team, how do you do that? Data drift.

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