A package to help developers build front end user interfaces for machine learning models.
Project description
*This package is intended to help developers quickly build scalable and customisable front end user interfaces for machine learning models. You can start using this package by following these 5 easy steps:*
<br/> <br/>
*Step 1: Install and Setup*
1.1. Open up a new working directory and create a virtual environment by running this command python -m venv env on the comand prompt. <br/>
1.2. Run envScriptsactivate to activate the virtual environment. <br/>
1.3. Install the Django machine learning user interface package by running pip install django-machine-learning-user-interface. <br/>
1.4. Run cd envLibsite-packagessrc to find the package files. <br/>
1.5. Open up the files on a code editor e.g. VsCode. <br/>
1.6. Intall project requirments by running pip install -r requirements.txt on the comand prompt. <br/> <br/>
*Step 2: Secrete Key*
2.1. Genrate a secrete key. You can use get one here: https://djecrety.ir/. <br/>
2.2. Create a .env file in src and store you secrte key inside. <br/>
2.3. Make sure to label it SECRET_KEY. <br/> <br/>
*Step 3: Inputs*
3.1. Navigate to srcinput. <br/>
3.2. Inside the input file create a folder and call it model then copy your pickle model file (e.g ‘titanic.pkl’) into this folder. <br/>
3.3. In the forms.py file populate the class IndexForm as specified in the code comments. <br/>
3.4. In the params.py file specify the name of the target variable (e.g. ‘Passenger Status’) and the name of the model (e.g ‘titanic.pkl’). <br/> <br/>
*Step 4: Views*
4.1. Navigate to srcinterfaceviews.py. <br/>
4.2. Add the cleaned form data as specified (line 21). <br/>
4.3. List the x variables as specified (line 30). <br/>
4.4. If your model is a classification model, edit line 41 as specified. <br/> <br/>
*Step 5: Generate the UserInterface*
5.1. On the comand prompt run python manage.py runserver. <br/>
5.2. Go to local host on your browser(http://127.0.0.1:8000/) and you should see your application and be able to interact with your application. <br/>
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file django-machine-learning-user-interface-0.0.0.18.tar.gz.
File metadata
- Download URL: django-machine-learning-user-interface-0.0.0.18.tar.gz
- Upload date:
- Size: 8.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9b30f91b8b08b94dd82a051b71283240301065ee7601c5644d75600aa3fd6c81
|
|
| MD5 |
397d1eff0931c7fcfce1d48f8c289442
|
|
| BLAKE2b-256 |
6eb3b1015f2e70b83e456f295c49c9a88677cd913bd450aac71bede8dcf376be
|
File details
Details for the file django_machine_learning_user_interface-0.0.0.18-py3-none-any.whl.
File metadata
- Download URL: django_machine_learning_user_interface-0.0.0.18-py3-none-any.whl
- Upload date:
- Size: 12.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c7e5406c77f8711c646c53f6ef169d212109e7d6df17e9be6986cc8c8f631b73
|
|
| MD5 |
4fddb25230ad0b599be53f5f2c3d9380
|
|
| BLAKE2b-256 |
565ab3956419681cbd059de2824008bf5c5eb5d2a3ae23640e75c8eac5188fa8
|