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5 Lessons

Model Deployment and MLOps

Focus on this chapter's key concepts. Dive into each topic for a detailed understanding with examples and structured notes.

Hyperparameter tuning (Grid Search, Random Search, Bayesian opimization)

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1 of 5 Lessons

Saving and loading models (Pickle, Joblib, ONNX)

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2 of 5 Lessons

Creating REST APIs with Flask or FastAPI

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3 of 5 Lessons

Containerization with Docker

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4 of 5 Lessons

Model monitoring (Data drift and concept drift)

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5 of 5 Lessons

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Model Deployment and MLOps - Advanced Machine Learning | MBA Business Analytics