项目作者: nialdaly

项目描述 :
Model hyperparameter tuning with SageMaker & TensorFlow
高级语言: Jupyter Notebook
项目地址: git://github.com/nialdaly/sagemaker-tf-hpt.git
创建时间: 2021-01-27T19:57:09Z
项目社区:https://github.com/nialdaly/sagemaker-tf-hpt

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Model Hyperparameter Tuning with SageMaker & TensorFlow

This project covers model hyperparameter tuning (HPT) across a number of different deep learning problems/datasets using TensorFlow and Amazon SageMaker. Hyperparameter tuning works by finding the best version of a model by running many training jobs on your dataset using the algorithm and ranges of hyperparameters that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by a metric that you choose.

A conda_tensorflow2_p36 kernel was used with the Amazon SageMaker notebook instance.

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