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# IRIS classification task with AWS Lambda | |
Workflow: use of AWS lambda function for deployment | |
### Training the model: | |
bash | |
> python train.py | |
### Building the docker image: | |
bash | |
> docker build -t iris-classification-lambda . | |
### Running the docker container locally: | |
bash | |
> docker run --name iris-classification-lambda-cont -p 8080:8080 iris-classification-lambda | |
### Testing locally: | |
Example of a prediction request | |
bash | |
> curl -X POST "http://localhost:8080/2015-03-31/functions/function/invocations" -H "Content-Type: application/json" -d '{"features": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]}' | |
python | |
> python3 inference_api.py --url http://localhost:8080/2015-03-31/functions/function/invocations -d '{"features": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]}' | |
### Deployment to AWS | |
Steps: | |
- Pushing the docker container to AWS ECR | |
- Creating and testing a Lambda function | |
- Creating an API via API Gateway |