# 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.