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Build, Train, and Deploy Machine Learning Models with Amazon SageMaker

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大小
432.5 MB
文件数
99
分类
视频
热度
152
最近活跃
1 小时前

文件列表

  • 01. Course Overview/01. Course Overview.mp42.8 MB
  • 01. Course Overview/01. Course Overview.srt2.6 KB
  • 02. Getting Started with AWS SageMaker/01. Introduction.mp41.2 MB
  • 02. Getting Started with AWS SageMaker/01. Introduction.srt1.2 KB
  • 02. Getting Started with AWS SageMaker/02. Course Scenario.mp41.8 MB
  • 02. Getting Started with AWS SageMaker/02. Course Scenario.srt1.3 KB
  • 02. Getting Started with AWS SageMaker/03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.mp42.8 MB
  • 02. Getting Started with AWS SageMaker/03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.srt2.7 KB
  • 02. Getting Started with AWS SageMaker/04. Introduction to AWS SageMaker.mp46.6 MB
  • 02. Getting Started with AWS SageMaker/04. Introduction to AWS SageMaker.srt7.9 KB
  • 02. Getting Started with AWS SageMaker/05. Setting up AWS SageMaker.mp49.4 MB
  • 02. Getting Started with AWS SageMaker/05. Setting up AWS SageMaker.srt6.9 KB
  • 02. Getting Started with AWS SageMaker/06. Summary.mp41.4 MB
  • 02. Getting Started with AWS SageMaker/06. Summary.srt2.0 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/01. Introduction.mp4862.1 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/01. Introduction.srt874 B
  • 03. Building Machine Learning Models Using AWS SageMaker/02. SageMaker Notebook Instances.mp41.7 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/02. SageMaker Notebook Instances.srt2.0 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/03. Creating a Notebook Instance.mp46.7 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/03. Creating a Notebook Instance.srt5.2 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/04. Overview of the Image Classification Built-in Algorithm.mp44.6 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/04. Overview of the Image Classification Built-in Algorithm.srt5.6 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/05. Obtaining, Exploring, and Preprocessing Histopathology Images.mp428.4 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/05. Obtaining, Exploring, and Preprocessing Histopathology Images.srt18.2 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.mp418.3 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.srt15.1 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.mp45.7 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.srt4.0 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/08. Overview of Using Tensorflow in SageMaker.mp43.5 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/08. Overview of Using Tensorflow in SageMaker.srt4.5 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/09. Converting Images to the TFRecord Format.mp410.3 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/09. Converting Images to the TFRecord Format.srt7.2 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.mp428.7 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.srt17.8 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/11. Overview of Using Apache MXNet in SageMaker.mp42.4 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/11. Overview of Using Apache MXNet in SageMaker.srt2.9 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.mp429.9 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.srt20.4 KB
  • 03. Building Machine Learning Models Using AWS SageMaker/13. Summary.mp41.6 MB
  • 03. Building Machine Learning Models Using AWS SageMaker/13. Summary.srt1.9 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/01. Introduction.mp41011.4 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/01. Introduction.srt1.1 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/02. Overview of Creating Training Jobs in SageMaker.mp44.8 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/02. Overview of Creating Training Jobs in SageMaker.srt6.0 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/03. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp420.1 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/03. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt12.5 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/04. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp411.4 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/04. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt7.6 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/05. Creating and Monitoring a Training Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp411.5 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/05. Creating and Monitoring a Training Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt7.7 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/06. Creating and Monitoring a Training Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.mp411.7 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/06. Creating and Monitoring a Training Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.srt7.2 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/07. Overview of Automatic Hyperparameter Optimization.mp43.2 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/07. Overview of Automatic Hyperparameter Optimization.srt3.3 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/08. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp422.8 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/08. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt18.6 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/09. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp411.7 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/09. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt7.1 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/10. Creating and Monitoring a Tuning Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp411.8 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/10. Creating and Monitoring a Tuning Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt7.6 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/11. Creating and Monitoring a Tuning Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.mp414.3 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/11. Creating and Monitoring a Tuning Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.srt7.4 KB
  • 04. Training Machine Learning Models Using AWS SageMaker/12. Summary.mp41.2 MB
  • 04. Training Machine Learning Models Using AWS SageMaker/12. Summary.srt1.4 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/01. Introduction.mp41.7 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/01. Introduction.srt1.7 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/02. Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services.mp42.0 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/02. Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services.srt2.6 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/03. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp422.1 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/03. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt13.5 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/04. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp415.1 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/04. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt7.6 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/05. Deploying and Testing the Trained Model Based on a Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp413.7 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/05. Deploying and Testing the Trained Model Based on a Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt7.6 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/06. Deploying and Testing the Trained Model Based on a Custom Mxnet Algorithm Using the High-level SageMaker Python Library.mp414.4 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/06. Deploying and Testing the Trained Model Based on a Custom Mxnet Algorithm Using the High-level SageMaker Python Library.srt7.9 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/07. Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda.mp42.7 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/07. Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda.srt3.7 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.mp415.8 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.srt12.2 KB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/09. Summary.mp41.0 MB
  • 05. Deploying Machine Learning Models Using AWS SageMaker/09. Summary.srt1.2 KB
  • 06. Managing Security and Scalability in AWS SageMaker/01. Introduction.mp41.0 MB
  • 06. Managing Security and Scalability in AWS SageMaker/01. Introduction.srt1.1 KB
  • 06. Managing Security and Scalability in AWS SageMaker/02. Overview of Managing Authentication and Access Control Using IAM Policies.mp42.4 MB
  • 06. Managing Security and Scalability in AWS SageMaker/02. Overview of Managing Authentication and Access Control Using IAM Policies.srt2.9 KB
  • 06. Managing Security and Scalability in AWS SageMaker/03. Configuring Access Control to Notebook Instances.mp422.4 MB
  • 06. Managing Security and Scalability in AWS SageMaker/03. Configuring Access Control to Notebook Instances.srt16.4 KB
  • 06. Managing Security and Scalability in AWS SageMaker/04. Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch.mp42.7 MB
  • 06. Managing Security and Scalability in AWS SageMaker/04. Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch.srt3.3 KB
  • 06. Managing Security and Scalability in AWS SageMaker/05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.mp47.1 MB
  • 06. Managing Security and Scalability in AWS SageMaker/05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.srt4.2 KB
  • 06. Managing Security and Scalability in AWS SageMaker/06. Overview of Configuring Automatic Scaling for AWS SageMaker Endpoints.mp41.3 MB
  • 06. Managing Security and Scalability in AWS SageMaker/06. Overview of Configuring Automatic Scaling for AWS SageMaker Endpoints.srt1.7 KB
  • 06. Managing Security and Scalability in AWS SageMaker/07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.mp46.3 MB
  • 06. Managing Security and Scalability in AWS SageMaker/07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.srt4.2 KB
  • 06. Managing Security and Scalability in AWS SageMaker/08. Summary.mp41.2 MB
  • 06. Managing Security and Scalability in AWS SageMaker/08. Summary.srt1.6 KB
  • aws-sagemaker-machine-learning-models.zip5.2 MB

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