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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The examples available in this repository cover several processing steps, from pre-processing, processing and post-processing. The methods already available are described below.
You can run the methods in two ways:
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.gitYou can run online on Google Colab or Binder.
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.
The MIT License (MIT). Please see License File for more information.