This document discusses building an image classification model using Amazon SageMaker and deploying it via an API Gateway and Lambda function. Key steps include:
1. Developing a Python Lambda function to preprocess images from API requests and call a SageMaker endpoint for predictions.
2. Creating an IAM role for the Lambda function to access SageMaker.
3. Building and deploying the SageMaker model.
4. Configuring API Gateway to invoke the Lambda function via a REST API, with the Lambda function returning classification results.
This allows building and deploying a machine learning model on SageMaker and serving predictions through a serverless API for image classification.
This document discusses building an image classification model using Amazon SageMaker and deploying it via an API Gateway and Lambda function. Key steps include:
1. Developing a Python Lambda function to preprocess images from API requests and call a SageMaker endpoint for predictions.
2. Creating an IAM role for the Lambda function to access SageMaker.
3. Building and deploying the SageMaker model.
4. Configuring API Gateway to invoke the Lambda function via a REST API, with the Lambda function returning classification results.
This allows building and deploying a machine learning model on SageMaker and serving predictions through a serverless API for image classification.
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