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# IRIS classification task with AWS Lambda | |
## Workflow: use of AWS lambda function for deployment | |
Steps to Deploy | |
### Training the Model: | |
bash | |
> python train.py | |
### Building the docker image: | |
bash | |
> docker build -t iris-lambda . | |
### Running the docker container locally: | |
bash | |
> docker run --name iris-lambda-cont -p 8080:8080 iris-lambda | |
### Testing locally: | |
Use a tool like curl to send a test request: | |
bash | |
> curl -XPOST "http://localhost:8080/2015-03-31/functions/function/invocations" -d '{"body": "{\"features\": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]}"}' | |
Deploy to AWS Lambda: Package the code and dependencies, then upload to AWS Lambda via the AWS Management Console or AWS CLI. | |
This setup provides a complete pipeline from training the model to deploying it on AWS Lambda. | |