Titlebook: Beginning MLOps with MLFlow; Deploy Models in AWS Sridhar Alla,Suman Kalyan Adari Book 2021 Sridhar Alla, Suman Kalyan Adari 2021 Machine L

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evince

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Introduction to MLFlow, will cover how you can integrate MLFlow with scikit-learn, TensorFlow 2.0+/Keras, PyTorch, and PySpark. We will go over experiment creation; metric, parameter, and artifact logging; model logging; and how you can deploy models on a local server and query them for predictions.

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Melanocytes

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Manar Alohaly,Hassan Takabi,Eduardo BlancoIn this chapter, we will cover how you can operationalize your MLFlow models using AWS SageMaker. We will cover how you can upload your runs to S3 storage, how you can build and push an MLFlow Docker container image to AWS, and how you can deploy your model, query it, update the model once it is deployed, and remove a deployed model.

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effrontery

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Getting Started: Data Analysis,In this chapter, we will go over the premise of the problem we are attempting to solve with the machine learning solution we want to operationalize. We will also begin data analysis and feature engineering of our data set.