Framework that uses artificial intelligence applied to mathematical models to make predictions

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Deep LearningLiconIA
Overview

LiconIA

Framework that uses artificial intelligence applied to mathematical models to make predictions

GitHub Release GitHub license


Interface Overview

image

Table of contents

[TOC]


1 Articles, theses for technical support

1.1 Final Coursework



1.2 Dissertation



1.3 Theses


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1.4 Articles



2 Requirements


  • Python 3.6 or superior (sudo apt-get install python3.6 under Linux)
  • Python virtual environment (sudo apt-get install python3.6-venv under Linux)

3 Package structure (need to update)


The initial directory structure should look like this:


4 Development and Tests

4.1 Installing the package


Start by creating a new virtual environment for your project. Next, update the packages pip and setuptools to the latest version. Then install the package itself.

$ sudo apt-get install python3-tk
$ /usr/bin/python3.6 -m venv --prompt="LiconIA" venv
$ source venv/bin/activate
(LiconIA) $ pip install --upgrade setuptools pip
(LiconIA) $ pip install numpy matplotlib pandas xlrd PyQt5
(LiconIA) $ pip install xlrd==1.2.0

4.2 Run program


To run the code just type:

$ python run.py

4.3 Qt-desing Information


Information about running the interface in qt-desing https://pythonbasics.org/qt-designer-python/

How to start Designer

$ cd /usr/lib/x86_64-linux-gnu/qt5/bin/ && ./designer
$ ./designer

Information about widgets the interface in qt-desing https://doc.qt.io/qtforpython/PySide2/QtWidgets/

Convert ui to py

pyuic5 /home/linux/helloworld.ui -o helloworld.py

4.4 Code checking


It is also possible to check for errors in Python code using:

use a pep8 -> pycodestyle


4.5 Development Team



5 License


This package is released and distributed under the license GNU GPL Version 3, 29 June 2007.

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