This is a graphical software for educational and academic purposes to
make it easier for people to learn Artificial Intelligence (AI),
Machine Learning (ML), and maybe even data visualization.
This software is designed to help people to learn the Artificial Intelligence quickly and also enables users to quickly prototype their AI/ML models. Teaches people different kinds of models and how ML works and not get confused between AI, Neural Network, and ML as I orignally did.
The core principles of this software is: Flexibility, Simplicity, and Productive. From begginers to experts, domain-specific to programmer, acedemic to industry, we try to fit all of them into a nice little app for everyone to use.
The purpose of this software is to bridge the gap between the domain experts (i.e. mathematicians, designer) to the programmers who programs on Python or C++ that has a large and extensive library to program any kinds of AI/ML models they may need.
Future goal of this project is so everyone uses Graphical Interface (not necessarily this project) to design the AI without any hassle to prior knowledge of programming. And also create a "lowish"-level AI designer to be a lot more flexible, creating a variety of AI models, hence the creation of this project. And its core principles: Flexibility and Simplicity.
This software is a visually-rich desktop application to utilize
the simplicity yet complexity of a graphic interface. Much like from
using Command Prompts in the DOS-era to load and manipulate files towards
the beggining of Graphic Interface to easily navigate file directories,
system settings, etc.
It uses nodes (a little elongated draggable square with inputs and outputs) to create the project. Each nodes has input and output connector which connects to output and input respectively. This allows the user to understand the relationship between the two nodes and the flow of data of which is the data is going towards. The user (constant) input on each nodes are to manipulate how the data from the connections gets manipulated for greater flexibility.
Pictures tells more words than a paragraph. As in this case, it does show some the rusty, messy, early development of this software.
An example of ML in GUI using Linear Regression on iris.csv.
- Access the zipped folder containing the executables via https://andrews236.github.io/
- Python 3.7 (x64) Interpreter; cannot be x86
- Libraries Required via requirements.txt
- Preferably use virtual-environment to execute your project
Goto CHANGELOG to see version history
Goto TODO to see the features currently getting implemented
Feature Request
GraphicalAI Copyright (C) 2020 Andrew Shen
This program comes with ABSOLUTELY NO WARRANTY; for details read LICENSE.
This is free software, and you are welcome to redistribute it
under certain conditions; for details read LICENSE.