Artificial Intelligence Methods and Techniques
This repository is under development and constantly being updated. Containing examples in Python of Artificial Intelligence applications, the Jupyter Nooteboks available aims to help mainly those who are starting in the AI area, with examples and links to reference materials.
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Table of Contents
Overview
The examples available in this repository cover several processing steps, from pre-processing, processing and post-processing. The methods already available are described below.
Pre-Processing
Processing
Pos-Processing
How To Use
You can run the methods in two ways:
Running Locally
Clone this repository to your machine and add it to your jupyter notebook path:
git clone https://github.com/jefmenegazzo/Artificial-Intelligence-Methods-and-Techniques.git
Running Online
You can run online on Google Colab or Binder.
Contributions
The repository is open to contributions in documentation, error fixes, improvements and addition of new methods. Currently, the theoretical explanation of the methods is referenced through links in the Jupyter Notebook. However, contributions are welcome to add the theoretical explanation of the AI methods and techniques together with the source-code in Jupyter Notebook.
License
The MIT License (MIT). Please see License File for more information.