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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书目名称Beginning MLOps with MLFlow影响因子(影响力)




书目名称Beginning MLOps with MLFlow影响因子(影响力)学科排名




书目名称Beginning MLOps with MLFlow网络公开度




书目名称Beginning MLOps with MLFlow网络公开度学科排名




书目名称Beginning MLOps with MLFlow被引频次




书目名称Beginning MLOps with MLFlow被引频次学科排名




书目名称Beginning MLOps with MLFlow年度引用




书目名称Beginning MLOps with MLFlow年度引用学科排名




书目名称Beginning MLOps with MLFlow读者反馈




书目名称Beginning MLOps with MLFlow读者反馈学科排名

evince

不要严酷

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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ALIBI

Melanocytes

Arb853

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.

anarchist

effrontery

柱廊

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.