aitk 2.0.0

Python tools for AI

aitk: Artificial Intelligence Toolkit

This collection contains two things: an open source set of Python tools, and a set of computational essays for exploring Artificial Intelligence, Machine Learning, and Robotics. This is a collaborative effort started by the authors, building on almost a century of collective experience in education and research.

The code and essays are designed to require as few computing resources as necessary, while still allowing readers to experience first-hand the topics covered.

Authors

• Douglas Blank - Emeritus Professor of Computer Science, Bryn Mawr College; Head of Research at Comet.ml
• Jim Marshall - Professor in the Computer Science Department at Sarah Lawrence College
• Lisa Meeden - Professor in the Computer Science Department at Swarthmore College

Contributors

Please feel free to contribute to this collection: https://github.com/ArtificialIntelligenceToolkit/aitk

• Your Name Here

Computational Essays

Each computational essay is described at Computational Essays.

Artifical Intelligence Toolkit

aitk is Python package containing the following modules.

• aitk - top level package
  • aitk.robots - for exploring simulated mobile robots, with cameras and sensors
  • aitk.algorithms - for exploring algorithms
  • aitk.networks - for constructing and visualizing Keras deep learning models
  • aitk.utils - for common utilities

Python Installation

Using pip

If you already have an environment for running Python, and optionally Jupyter Notebooks, you can simply execute this at the command line:

pip install aitk

If you haven't install Jupyter (and are not running in Google's colab), jump down to "Jupyter Installation".

If you are inside a notebook (say on Google's colab):

%pip install aitk --quiet

Using conda

If you are setting up your own Jupyter Notebook environment on your own computer, we recommend using miniconda.

To use miniconda:

1. First install miniconda
2. Next, activate your base environment: source ~/miniconda/bin/activate
3. Create a Python 3.8 conda environment: conda create --name py38 python=3.8
4. Activate it: conda activate py38

You only need to do step 1 once. To get out of conda, back to your regular system:

• conda deactivate (will get out of py38)
• conda deactivate (will get out of base environment)

Software Installation

After activating your conda environment:

1. pip install "aitk[jupyter]" (installs all of the requirements to run in Jupyter Lab 3.0)
2. pip install pandas tensorflow numpy matplotlib tqdm ipycanvas (some things you might want)

Jupyter Installation

If you want to work in notebooks and jupyter lab:

1. pip install jupyterlab
2. jupyter labextension install @jupyter-widgets/jupyterlab-manager ipycanvas
3. jupyter lab starts it up, opens browser window

AITK Community

For questions and comments, please use https://github.com/ArtificialIntelligenceToolkit/aitk/discussions/