https://github.com/geekquad/flower-prediction

Basic Iris Flower Prediction. Learning how to host ML models using Flask and deploy it using Heroku.
https://github.com/geekquad/flower-prediction

flask-application heroku iris ml

Last synced: 26 days ago
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Basic Iris Flower Prediction. Learning how to host ML models using Flask and deploy it using Heroku.

• Host: GitHub
• URL: https://github.com/geekquad/flower-prediction
• Owner: geekquad
• Created: 2020-11-28T10:38:45.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2020-11-29T09:42:19.000Z (about 4 years ago)
• Last Synced: 2024-11-10T08:43:38.455Z (3 months ago)
• Topics: flask-application, heroku, iris, ml
• Language: HTML
• Homepage: https://irisforecast.herokuapp.com/
• Size: 4.62 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Flower-Prediction

Basic Iris Flower Predcition.

Trained using Support Vector Machine Algorithm. 

Learning how to deploy ML models using Flask. 

### Setup:

1. Clone the repo:

```

$ git clone https://github.com/geekquad/Flower-Prediction.git

``` 

2. Activate Environment:

```

$ python3 -m venv env

```

3. Install dependencies:

```

$ pip install -r requirements.txt

```

4. Run Flask server using

```

$ python app.py

```