https://github.com/ayberkyavuz/ml_model_server_docker_deployment

This repository is for containing source codes of machine learning model server deployment.
https://github.com/ayberkyavuz/ml_model_server_docker_deployment

deployment docker flask machine-learning model python random-forest scikit-learn

Last synced: 6 days ago
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This repository is for containing source codes of machine learning model server deployment.

• Host: GitHub
• URL: https://github.com/ayberkyavuz/ml_model_server_docker_deployment
• Owner: AyberkYavuz
• Created: 2021-11-11T14:40:55.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2021-12-01T13:56:56.000Z (about 3 years ago)
• Last Synced: 2024-12-06T18:37:52.001Z (2 months ago)
• Topics: deployment, docker, flask, machine-learning, model, python, random-forest, scikit-learn
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ml_model_server_docker_deployment

This repository is for containing source codes of machine learning model server deployment.

## Prerequisite

You need to have [docker](https://www.docker.com/products/docker-desktop)

## Youtube Video of The Project

[![IMAGE ALT TEXT HERE](http://img.youtube.com/vi/deFb1Y4XTXY/0.jpg)](http://www.youtube.com/watch?v=deFb1Y4XTXY)

## Docker Deployment Instructions

1. clone this repo to your local machine

2. open terminal

3. cd /path/to/ml_model_server_docker_deployment

4. start docker

5. use the following command to build the docker image

```bash

docker image build -t docker-iris-ml-server .

```

6. use the following command to see docker images

```bash

docker image ls

```

7. use the following command to run ml server

```bash

docker run -p 5000:5000 -d docker-iris-ml-server

```

8. open http://localhost:5000/predict_class in your browser to see get method message

9. open postman and try http://localhost:5000/predict_class for the post method to get model prediction

For example; try the following in your POST request to get machine learning model prediction

```bash

{"sepal_length": 5.1, "sepal_width": 3.5, 

"petal_length": 1.4, "petal_width": 0.2}

```

10. use the following command to see CONTAINER ID

```bash

docker ps

```

11. copy CONTAINER ID

12. use the following command to stop docker container

```bash

docker stop "CONTAINER ID"

```

13. use the following command to free up all the resources that the docker container uses

```bash

docker system prune

```