https://github.com/kavindulakmal/flask_ml_web_app
Use a Machine Learning Model with Python Flask
https://github.com/kavindulakmal/flask_ml_web_app
flask linear-regression machine-learning python
Last synced: 3 months ago
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Use a Machine Learning Model with Python Flask
- Host: GitHub
- URL: https://github.com/kavindulakmal/flask_ml_web_app
- Owner: Kavindulakmal
- Created: 2023-10-29T10:12:44.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-29T11:07:17.000Z (over 2 years ago)
- Last Synced: 2025-09-13T03:43:05.627Z (10 months ago)
- Topics: flask, linear-regression, machine-learning, python
- Language: Jupyter Notebook
- Homepage:
- Size: 109 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Security: SECURITY.md
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README
## Machine Learning Web Application With Flask
This is a project to elaborate how to use a Machine Learning model using Flask API
### Prerequisites
You must have
1. click==7.1.2
2. itsdangerous==1.1.0
3. Jinja2==2.11.3
4. joblib==1.0.1
5. kaleido==0.2.1
6. MarkupSafe==1.1.1
7. numpy==1.20.2
8. pandas==1.2.3
9. plotly==4.14.3
10. python-dateutil==2.8.1
11. pytz==2021.1
12. retrying==1.3.3
13. scikit-learn==0.24.1
14. scipy==1.6.2
15. six==1.15.0
16. threadpoolctl==2.1.0
17. Werkzeug==1.0.1(for Machine Learning Model) and Flask (for API) installed.
### Project Structure
inside app folder
1. app.py - This contains Flask APIs that receive employee details through API calls.
2. templates -This folder contains the HTML template (index.html) to allow the entry of details and display the predicted graph.
3. static - This folder contains the files that are downloaded images from the app.
### Running the project
1.Ensure that you are in the project home directory. Create the virtual environment by running the below command from the command prompt -
```
python -m venv .env
```
And activate virtual environment by running the below command from the command prompt
```
.env\Scripts\activate
```
2.Go to the `app` folder and run the below command from the command prompt
```
flask run
```
By default, flask will run on port 5000.
Navigate to URL http://127.0.0.1:5000/ (or) http://localhost:5000
You should be able to view the homepage.
Input a comma-separated list of age values like `1,2,17.4`.
If everything goes well, you should be able to see the predicted values on the HTML page!
### Contributing
Pull requests are welcomed. For major changes, please open an issue first to discuss what you would like to change. Thanks!
Happy Coding!!!
### Copyright
© KAVINDU™ | 2023