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A Simple IRIS Flower Classification Model Deployment project

The Iris Dataset contains four features (length and width of sepals and petals) of 50 samples of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). These measures were used to create a linear discriminant model to classify the species. The dataset is often used in data mining, classification and clustering examples and to test algorithms.

Building a Docker Image

 git clone https://github.com/eeveeta/docker-iris cd docker-iris docker image build -t eeveeta/docker-iris:1.0.0 . 

Running the container

 docker run --rm --name docker-iris -p 8080:8080 -d eeveeta/docker-iris:1.0.0 ` 

Accessing the app

Open browser http://localhost:8080/

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This is a simple iris flower classification model deployment project as flask app on Docker or Kubernetes.

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  • Python 57.3%
  • HTML 40.4%
  • Dockerfile 2.3%