https://github.com/baatout/ml-in-prod

Tutorial repo for the article "ML in Production"
https://github.com/baatout/ml-in-prod

Last synced: 3 months ago
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Tutorial repo for the article "ML in Production"

• Host: GitHub
• URL: https://github.com/baatout/ml-in-prod
• Owner: baatout
• Created: 2018-07-14T15:44:47.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-09-08T11:55:46.000Z (over 6 years ago)
• Last Synced: 2024-08-01T15:13:39.213Z (6 months ago)
• Language: Python
• Homepage: https://medium.com/contentsquare-engineering-blog/machine-learning-in-production-c53b43283ab1
• Size: 17.6 KB
• Stars: 12
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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• awesome - ml-in-prod - Tutorial repo for the article "ML in Production" (Python)

README

        
# ML in prod

#### A python predictive system design.

Article: https://medium.com/contentsquare-engineering-blog/machine-learning-in-production-c53b43283ab1

## Building the pipeline

```bash

$ cd training

$ python3 -m venv venv

$ source venv/bin/activate

$ pip install -r requirements.txt

$ python training.py

```

## Running the server

- If you did the previous steps then:

```bash

$ cd ../; deactivate

$ cd server

$ python3 -m venv venv

$ source venv/bin/activate

$ pip install -r requirements.txt

$ python run_server.py

```

## Making online predictions

Once the server is up and running you can send features via POST requests and then receive the corresponding prediction (0 or 1).

You can find an example of the request body in `server/post.json`:

```bash

$ curl -H "Content-Type: application/json" -X POST --data @post.json http://localhost:5000/predict

```