=========
django-ai
=========
.. image:: https://badge.fury.io/py/django-ai.svg
:target: https://badge.fury.io/py/django-ai
.. image:: https://travis-ci.org/math-a3k/django-ai.svg?branch=master
:target: https://travis-ci.org/math-a3k/django-ai
.. image:: https://codecov.io/gh/math-a3k/django-ai/branch/master/graph/badge.svg
:target: https://codecov.io/gh/math-a3k/django-ai
Artificial Intelligence for Django
==================================
``django-ai`` is a collection of apps for integrating statistical models into your
Django project so you can implement machine learning conveniently.
It integrates several libraries and engines providing your Django app with a set of
tools so you can leverage the data generated in your project.
.. image:: http://django-ai.readthedocs.io/en/latest/_images/django_ai.jpg
:target: https://django-ai.readthedocs.io/en/latest/introduction.html
Documentation
-------------
The full documentation is at https://django-ai.readthedocs.io or the `/docs` directory for offline reading.
Features
--------
* `Bayesian Networks <https://django-ai.readthedocs.io/en/latest/apps/bayesian_networks.html >`_: Integrate Bayesian Networks through your models using the `BayesPy framework <http://bayespy.org/>`_.
* `Spam Filtering <https://django-ai.readthedocs.io/en/latest/apps/spam_filtering.html>`_: Integrate Spam Filters to your Django project using the `scikit-learn framework <http://scikit-learn.org>`_.
* Bayesian Networks: Integrate Bayesian Networks through your models using the `BayesPy framework <http://bayespy.org/>`_.
See the `Introduction <https://django-ai.readthedocs.io/en/latest/introduction.html>`_ section in the documentation for more information.
Communication Channels
----------------------
* Mailing List: django-ai@googlegroups.com
* Chat: https://gitter.im/django-ai/django-ai
* GitHub: https://github.com/math-a3k/django-ai/issues
* Stack-Overflow: https://stackoverflow.com/questions/tagged/django-ai
* AI Stack Exchange: https://ai.stackexchange.com/questions/tagged/django-ai
Quickstart
----------
The easiest way of trying `django-ai` is inside its package:
1. Create a virtual environment and activate it::
python3 -m venv django-ai_env
source django-ai_env/bin/activate
2. Upgrade ``pip`` and install ``django-ai``::
(django-ai_env) pip install --upgrade pip
(django-ai_env) pip install django-ai
3. Change into the `django-ai` directory, i.e.::
(django-ai_env) cd django-ai_env/lib/python3.5/site-packages/django_ai
4. Create the migrations for the dependencies and apply them::
python manage.py makemigrations
python manage.py migrate
5. Create a superuser::
python manage.py createsuperuser
6. Start the development server and visit http://127.0.0.1:8000/admin/, look at the examples and start creating your statistical models::
python manage.py runserver
You can also clone it from the repository and install the requirements in a virtualenv::
git clone git@github.com:math-a3k/django-ai.git
and following the previous steps, install the requirements - ``pip install -r requirements.txt`` - in a virtual environment instead of the package.
For installing it in your project, please refer `here <https://django-ai.readthedocs.io/en/latest/installation.html>`_.
Running Tests
-------------
Does the code actually work?
::
source <YOURVIRTUALENV>/bin/activate
(myenv) $ pip install -r requirements_test.txt
(myenv) $ PYTHONHASHSEED=0 python runtests.py
django-ai
=========
.. image:: https://badge.fury.io/py/django-ai.svg
:target: https://badge.fury.io/py/django-ai
.. image:: https://travis-ci.org/math-a3k/django-ai.svg?branch=master
:target: https://travis-ci.org/math-a3k/django-ai
.. image:: https://codecov.io/gh/math-a3k/django-ai/branch/master/graph/badge.svg
:target: https://codecov.io/gh/math-a3k/django-ai
Artificial Intelligence for Django
==================================
``django-ai`` is a collection of apps for integrating statistical models into your
Django project so you can implement machine learning conveniently.
It integrates several libraries and engines providing your Django app with a set of
tools so you can leverage the data generated in your project.
.. image:: http://django-ai.readthedocs.io/en/latest/_images/django_ai.jpg
:target: https://django-ai.readthedocs.io/en/latest/introduction.html
Documentation
-------------
The full documentation is at https://django-ai.readthedocs.io or the `/docs` directory for offline reading.
Features
--------
* `Bayesian Networks <https://django-ai.readthedocs.io/en/latest/apps/bayesian_networks.html >`_: Integrate Bayesian Networks through your models using the `BayesPy framework <http://bayespy.org/>`_.
* `Spam Filtering <https://django-ai.readthedocs.io/en/latest/apps/spam_filtering.html>`_: Integrate Spam Filters to your Django project using the `scikit-learn framework <http://scikit-learn.org>`_.
* Bayesian Networks: Integrate Bayesian Networks through your models using the `BayesPy framework <http://bayespy.org/>`_.
See the `Introduction <https://django-ai.readthedocs.io/en/latest/introduction.html>`_ section in the documentation for more information.
Communication Channels
----------------------
* Mailing List: django-ai@googlegroups.com
* Chat: https://gitter.im/django-ai/django-ai
* GitHub: https://github.com/math-a3k/django-ai/issues
* Stack-Overflow: https://stackoverflow.com/questions/tagged/django-ai
* AI Stack Exchange: https://ai.stackexchange.com/questions/tagged/django-ai
Quickstart
----------
The easiest way of trying `django-ai` is inside its package:
1. Create a virtual environment and activate it::
python3 -m venv django-ai_env
source django-ai_env/bin/activate
2. Upgrade ``pip`` and install ``django-ai``::
(django-ai_env) pip install --upgrade pip
(django-ai_env) pip install django-ai
3. Change into the `django-ai` directory, i.e.::
(django-ai_env) cd django-ai_env/lib/python3.5/site-packages/django_ai
4. Create the migrations for the dependencies and apply them::
python manage.py makemigrations
python manage.py migrate
5. Create a superuser::
python manage.py createsuperuser
6. Start the development server and visit http://127.0.0.1:8000/admin/, look at the examples and start creating your statistical models::
python manage.py runserver
You can also clone it from the repository and install the requirements in a virtualenv::
git clone git@github.com:math-a3k/django-ai.git
and following the previous steps, install the requirements - ``pip install -r requirements.txt`` - in a virtual environment instead of the package.
For installing it in your project, please refer `here <https://django-ai.readthedocs.io/en/latest/installation.html>`_.
Running Tests
-------------
Does the code actually work?
::
source <YOURVIRTUALENV>/bin/activate
(myenv) $ pip install -r requirements_test.txt
(myenv) $ PYTHONHASHSEED=0 python runtests.py
Metadata
Release files for django-ai 0.0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| django_ai-0.0.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Release files / django_ai-0.0.2.1-py3-none-any.whl
| Download URL | django_ai-0.0.2.1-py3-none-any.whl |
|---|---|
| Size | 105.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
32e7eef83fee130a2be670635c0bba5682e18a1f5fb45d69f41a75546307c1dc
|
|
BLAKE2b-256 checksum How to use checksums |
58e439d5f4bc2a281079d0c0b06f02d533c6c52fe420c3aab38179e46790fb0e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |