ML-Ops Demo/Assignment
This repository contains code which demonstrates ML-Ops using a FastAPI application which predicts the flower class using the IRIS dataset (https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html)
Running Instructions
Create a fork of the repo using the fork button. Clone your fork using git clone https://www.github.com//mlops-iris.git Install dependencies using pip3 install -r requirements.txt Run application using python3 main.py Run tests using pytest
CI/CD
build (test) for all the pull requests build (test) and upload_zip for all pushes
Assignment Tasks
1.Change this README to add your name here: . Add and commit changes to a new branch and create a pull request ONLY TO YOUR OWN FORK to see the CI/CD build happening. If the build succeeds, merge the pull request with master and see the CI/CD upload_zip take place. 2.Add 2 more unit tests of your choice to test_app.py and make sure they are passing. 3.Add one more classifier to startup and use only the one with better accuracy. 4.Add the attribute timestamp to the response and return the current time with it.