03. Building Machine Learning Models Using AWS SageMaker/12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.mp4 31.4 MB
03. Building Machine Learning Models Using AWS SageMaker/10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.mp4 30.1 MB
03. Building Machine Learning Models Using AWS SageMaker/05. Obtaining, Exploring, and Preprocessing Histopathology Images.mp4 29.8 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.mp4 23.9 MB
06. Managing Security and Scalability in AWS SageMaker/03. Configuring Access Control to Notebook Instances.mp4 23.5 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.mp4 23.2 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.mp4 21.1 MB
03. Building Machine Learning Models Using AWS SageMaker/06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.mp4 19.2 MB
05. Deploying Machine Learning Models Using AWS SageMaker/08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.mp4 16.5 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.mp4 15.8 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.mp4 15.1 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.mp4 15.0 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.mp4 14.4 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.mp4 12.4 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.mp4 12.3 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.mp4 12.2 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.mp4 12.1 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.mp4 11.9 MB
03. Building Machine Learning Models Using AWS SageMaker/09. Converting Images to the TFRecord Format.mp4 10.8 MB
02. Getting Started with AWS SageMaker/05. Setting up AWS SageMaker.mp4 9.8 MB
06. Managing Security and Scalability in AWS SageMaker/05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.mp4 7.4 MB
03. Building Machine Learning Models Using AWS SageMaker/03. Creating a Notebook Instance.mp4 7.1 MB
02. Getting Started with AWS SageMaker/04. Introduction to AWS SageMaker.mp4 6.9 MB
06. Managing Security and Scalability in AWS SageMaker/07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.mp4 6.6 MB
03. Building Machine Learning Models Using AWS SageMaker/07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.mp4 5.9 MB
aws-sagemaker-machine-learning-models.zip 5.4 MB
04. Training Machine Learning Models Using AWS SageMaker/02. Overview of Creating Training Jobs in SageMaker.mp4 5.1 MB
03. Building Machine Learning Models Using AWS SageMaker/04. Overview of the Image Classification Built-in Algorithm.mp4 4.8 MB
03. Building Machine Learning Models Using AWS SageMaker/08. Overview of Using Tensorflow in SageMaker.mp4 3.7 MB
04. Training Machine Learning Models Using AWS SageMaker/07. Overview of Automatic Hyperparameter Optimization.mp4 3.3 MB
02. Getting Started with AWS SageMaker/03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.mp4 3.0 MB
06. Managing Security and Scalability in AWS SageMaker/01. Introduction.mp4 1.1 MB
04. Training Machine Learning Models Using AWS SageMaker/01. Introduction.mp4 1.0 MB
03. Building Machine Learning Models Using AWS SageMaker/01. Introduction.mp4 882.8 kB
03. Building Machine Learning Models Using AWS SageMaker/12. Configuring a MXNet Estimator Using the High-level SageMaker Python Library.srt 20.9 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.srt 19.0 kB
03. Building Machine Learning Models Using AWS SageMaker/05. Obtaining, Exploring, and Preprocessing Histopathology Images.srt 18.6 kB
03. Building Machine Learning Models Using AWS SageMaker/10. Configuring a Tensorflow Estimator Using the High-level SageMaker Python Library.srt 18.2 kB
06. Managing Security and Scalability in AWS SageMaker/03. Configuring Access Control to Notebook Instances.srt 16.7 kB
03. Building Machine Learning Models Using AWS SageMaker/06. Configuring the Image Classification Algorithm Using the Low-level AWS SDK for Python.srt 15.5 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.srt 13.8 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.srt 12.8 kB
05. Deploying Machine Learning Models Using AWS SageMaker/08. Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda.srt 12.5 kB
02. Getting Started with AWS SageMaker/04. Introduction to AWS SageMaker.srt 8.1 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.srt 8.1 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.srt 7.9 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.srt 7.8 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.srt 7.8 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.srt 7.8 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.srt 7.8 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.srt 7.5 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.srt 7.4 kB
03. Building Machine Learning Models Using AWS SageMaker/09. Converting Images to the TFRecord Format.srt 7.4 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.srt 7.3 kB
02. Getting Started with AWS SageMaker/05. Setting up AWS SageMaker.srt 7.0 kB
04. Training Machine Learning Models Using AWS SageMaker/02. Overview of Creating Training Jobs in SageMaker.srt 6.2 kB
03. Building Machine Learning Models Using AWS SageMaker/04. Overview of the Image Classification Built-in Algorithm.srt 5.8 kB
03. Building Machine Learning Models Using AWS SageMaker/03. Creating a Notebook Instance.srt 5.4 kB
03. Building Machine Learning Models Using AWS SageMaker/08. Overview of Using Tensorflow in SageMaker.srt 4.6 kB
06. Managing Security and Scalability in AWS SageMaker/07. Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console.srt 4.3 kB
06. Managing Security and Scalability in AWS SageMaker/05. Analyzing Endpoint Metrics and Logs with AWS CloudWatch.srt 4.3 kB
03. Building Machine Learning Models Using AWS SageMaker/07. Configuring the Image Classification Algorithm Using the High-level SageMaker Python Library.srt 4.1 kB
05. Deploying Machine Learning Models Using AWS SageMaker/07. Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda.srt 3.7 kB
04. Training Machine Learning Models Using AWS SageMaker/07. Overview of Automatic Hyperparameter Optimization.srt 3.4 kB
06. Managing Security and Scalability in AWS SageMaker/04. Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch.srt 3.3 kB
03. Building Machine Learning Models Using AWS SageMaker/11. Overview of Using Apache MXNet in SageMaker.srt 3.0 kB
06. Managing Security and Scalability in AWS SageMaker/02. Overview of Managing Authentication and Access Control Using IAM Policies.srt 3.0 kB
02. Getting Started with AWS SageMaker/03. Overview of How the Sample REST API for Breast Cancer Detection Should Work.srt 2.7 kB
05. Deploying Machine Learning Models Using AWS SageMaker/02. Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services.srt 2.7 kB