Build, Train, and Deploy Machine Learning Models with Amazon SageMaker
01. Course Overview
01. Course Overview.mp4- 2.8 MB
01. Course Overview.srt- 2.58 KB
02. Getting Started with AWS SageMaker
01. Introduction.mp4- 1.2 MB
01. Introduction.srt- 1.17 KB
02. Course Scenario.mp4- 1.77 MB
02. Course Scenario.srt- 1.32 KB
03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.mp4- 2.84 MB
03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.srt- 2.68 KB
04. Introduction to AWS SageMaker.mp4- 6.61 MB
04. Introduction to AWS SageMaker.srt- 7.92 KB
05. Setting up AWS SageMaker.mp4- 9.37 MB
05. Setting up AWS SageMaker.srt- 6.86 KB
06. Summary.mp4- 1.43 MB
06. Summary.srt- 1.99 KB
03. Building Machine Learning Models Using AWS SageMaker
01. Introduction.mp4- 862.1 KB
01. Introduction.srt- 874 B
02. SageMaker Notebook Instances.mp4- 1.74 MB
02. SageMaker Notebook Instances.srt- 1.98 KB
03. Creating a Notebook Instance.mp4- 6.74 MB
03. Creating a Notebook Instance.srt- 5.24 KB
04. Overview of the Image Classification Built-in Algorithm.mp4- 4.59 MB
04. Overview of the Image Classification Built-in Algorithm.srt- 5.63 KB
05. Obtaining, Exploring, and Preprocessing Histopathology Images.mp4- 28.37 MB
05. Obtaining, Exploring, and Preprocessing Histopathology Images.srt- 18.18 KB
06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.mp4- 18.31 MB
06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.srt- 15.15 KB
07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.mp4- 5.67 MB
07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.srt- 3.99 KB
08. Overview of Using Tensorflow in SageMaker.mp4- 3.5 MB
08. Overview of Using Tensorflow in SageMaker.srt- 4.53 KB
09. Converting Images to the TFRecord Format.mp4- 10.28 MB
09. Converting Images to the TFRecord Format.srt- 7.19 KB
10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.mp4- 28.69 MB
10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.srt- 17.77 KB
11. Overview of Using Apache MXNet in SageMaker.mp4- 2.43 MB
11. Overview of Using Apache MXNet in SageMaker.srt- 2.9 KB
12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.mp4- 29.91 MB
12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.srt- 20.39 KB
13. Summary.mp4- 1.58 MB
13. Summary.srt- 1.86 KB
04. Training Machine Learning Models Using AWS SageMaker
01. Introduction.mp4- 1011.42 KB
01. Introduction.srt- 1.06 KB
02. Overview of Creating Training Jobs in SageMaker.mp4- 4.83 MB
02. Overview of Creating Training Jobs in SageMaker.srt- 6.03 KB
03. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp4- 20.13 MB
03. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt- 12.49 KB
04. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp4- 11.39 MB
04. Creating and Monitoring a Training Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt- 7.63 KB
05. Creating and Monitoring a Training Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp4- 11.5 MB
05. Creating and Monitoring a Training Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt- 7.7 KB
06. Creating and Monitoring a Training Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.mp4- 11.67 MB
06. Creating and Monitoring a Training Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.srt- 7.25 KB
07. Overview of Automatic Hyperparameter Optimization.mp4- 3.17 MB
07. Overview of Automatic Hyperparameter Optimization.srt- 3.27 KB
08. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp4- 22.76 MB
08. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt- 18.57 KB
09. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp4- 11.74 MB
09. Creating and Monitoring a Tuning Job for the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt- 7.09 KB
10. Creating and Monitoring a Tuning Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp4- 11.79 MB
10. Creating and Monitoring a Tuning Job for the Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt- 7.59 KB
11. Creating and Monitoring a Tuning Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.mp4- 14.29 MB
11. Creating and Monitoring a Tuning Job for the Custom MXnet Algorithm Using the High-level SageMaker Python Library.srt- 7.35 KB
12. Summary.mp4- 1.16 MB
12. Summary.srt- 1.43 KB
05. Deploying Machine Learning Models Using AWS SageMaker
01. Introduction.mp4- 1.66 MB
01. Introduction.srt- 1.71 KB
02. Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services.mp4- 2.01 MB
02. Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services.srt- 2.6 KB
03. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.mp4- 22.08 MB
03. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the Low-level AWS SDK for Python.srt- 13.5 KB
04. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.mp4- 15.08 MB
04. Deploying and Testing the Trained Model Based on the Built-in Image Classification Algorithm Using the High-level SageMaker Python Library.srt- 7.62 KB
05. Deploying and Testing the Trained Model Based on a Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.mp4- 13.7 MB
05. Deploying and Testing the Trained Model Based on a Custom Tensorflow Algorithm Using the High-level SageMaker Python Library.srt- 7.62 KB
06. Deploying and Testing the Trained Model Based on a Custom Mxnet Algorithm Using the High-level SageMaker Python Library.mp4- 14.42 MB
06. Deploying and Testing the Trained Model Based on a Custom Mxnet Algorithm Using the High-level SageMaker Python Library.srt- 7.92 KB
07. Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda.mp4- 2.71 MB
07. Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda.srt- 3.65 KB
08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.mp4- 15.76 MB
08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.srt- 12.22 KB
09. Summary.mp4- 1.05 MB
09. Summary.srt- 1.21 KB
06. Managing Security and Scalability in AWS SageMaker
01. Introduction.mp4- 1.03 MB
01. Introduction.srt- 1.09 KB
02. Overview of Managing Authentication and Access Control Using IAM Policies.mp4- 2.43 MB
02. Overview of Managing Authentication and Access Control Using IAM Policies.srt- 2.88 KB
03. Configuring Access Control to Notebook Instances.mp4- 22.42 MB
03. Configuring Access Control to Notebook Instances.srt- 16.35 KB
04. Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch.mp4- 2.72 MB
04. Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch.srt- 3.26 KB
05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.mp4- 7.05 MB
05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.srt- 4.16 KB
06. Overview of Configuring Automatic Scaling for AWS SageMaker Endpoints.mp4- 1.33 MB
06. Overview of Configuring Automatic Scaling for AWS SageMaker Endpoints.srt- 1.71 KB
07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.mp4- 6.26 MB
07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.srt- 4.16 KB
