Developed an end-to-end machine learning solution for predicting employee churn using Azure Databricks, leveraging Spark for data processing, MLflow for managing the ML workflow, and deploying the model using Databricks model serving.
George: Learning to Place Long-Lived Containers in Large Clusters with Operation Constraints
Model Serving with FastAPI
Lightweight model serving in Trusted Execution Environments.
This repository integrates ESM, EvolutionaryScale's protein language models, with the ExoStack platform to enable scalable AI-driven protein analysis, inference, and deployment.
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