# aitk: Artificial Intelligence Toolkit
[](https://zenodo.org/badge/latestdoi/339135763)
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](https://github.com/dsblank/) - Emeritus Professor of Computer Science, Bryn Mawr College; Head of Research at [Comet.ml](https://comet.ml/)
* [Jim Marshall](http://science.slc.edu/~jmarshall/) - Professor in the Computer Science Department at Sarah Lawrence College
* [Lisa Meeden](https://www.cs.swarthmore.edu/~meeden/) - Professor in the Computer Science Department at Swarthmore College
## Computational Essays
Each computational essay is described at [Computational Essays](https://github.com/ArtificialIntelligenceToolkit/aitk/blob/master/ComputationalEssays.md).
## Artifical Intelligence Toolkit
`aitk` is Python package containing the following modules.
* [aitk]() - top level package
* [aitk.robots](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/robots) - for exploring simulated mobile robots, with cameras and sensors
* [aitk.algorithms](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/algorithms/) - for exploring algorithms
* [aitk.networks](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/networks/) - for constructing and visualizing Keras deep learning models
* [aitk.utils](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/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](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)
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/
Raw data
{
"_id": null,
"home_page": "https://github.com/ArtificialIntelligenceToolkit/aitk",
"name": "aitk",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "ai, artificial intelligence, robots, simulator, jupyter, python, machine learning, neural networks, keras, tensorflow",
"author": "Douglas Blank",
"author_email": null,
"download_url": null,
"platform": "Linux",
"description": "# aitk: Artificial Intelligence Toolkit\n\n[](https://zenodo.org/badge/latestdoi/339135763)\n\nThis 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.\n\nThe code and essays are designed to require as few computing resources as necessary, while still allowing readers to experience first-hand the topics covered.\n\n## Authors\n\n* [Douglas Blank](https://github.com/dsblank/) - Emeritus Professor of Computer Science, Bryn Mawr College; Head of Research at [Comet.ml](https://comet.ml/)\n* [Jim Marshall](http://science.slc.edu/~jmarshall/) - Professor in the Computer Science Department at Sarah Lawrence College\n* [Lisa Meeden](https://www.cs.swarthmore.edu/~meeden/) - Professor in the Computer Science Department at Swarthmore College\n\n## Computational Essays\n\nEach computational essay is described at [Computational Essays](https://github.com/ArtificialIntelligenceToolkit/aitk/blob/master/ComputationalEssays.md).\n\n## Artifical Intelligence Toolkit\n\n`aitk` is Python package containing the following modules.\n\n* [aitk]() - top level package\n * [aitk.robots](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/robots) - for exploring simulated mobile robots, with cameras and sensors\n * [aitk.algorithms](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/algorithms/) - for exploring algorithms\n * [aitk.networks](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/networks/) - for constructing and visualizing Keras deep learning models\n * [aitk.utils](https://github.com/ArtificialIntelligenceToolkit/aitk/tree/master/docs/utils/) - for common utilities\n\n### Python Installation\n\n#### Using pip\n\nIf you already have an environment for running Python, and optionally\nJupyter Notebooks, you can simply execute this at the command line:\n\n```\npip install aitk\n```\n\nIf you haven't install Jupyter (and are not running in Google's\ncolab), jump down to \"Jupyter Installation\".\n\nIf you are inside a notebook (say on Google's colab):\n\n```\n%pip install aitk --quiet\n```\n\n#### Using conda\n\nIf you are setting up your own Jupyter Notebook environment on your\nown computer, we recommend using `miniconda`.\n\nTo use `miniconda`:\n\n1. First install [miniconda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)\n2. Next, activate your base environment: `source ~/miniconda/bin/activate`\n3. Create a Python 3.8 conda environment: `conda create --name py38 python=3.8`\n4. Activate it: `conda activate py38`\n\nYou only need to do step 1 once. To get out of conda, back to your regular system:\n\n* `conda deactivate` (will get out of py38)\n* `conda deactivate` (will get out of base environment)\n\n### Software Installation\n\nAfter activating your conda environment:\n\n1. `pip install \"aitk[jupyter]\"` (installs all of the requirements to run in Jupyter Lab 3.0)\n2. `pip install pandas tensorflow numpy matplotlib tqdm ipycanvas` (some things you might want)\n\n#### Jupyter Installation\n\nIf you want to work in notebooks and jupyter lab:\n\n1. `pip install jupyterlab`\n2. `jupyter labextension install @jupyter-widgets/jupyterlab-manager ipycanvas`\n3. `jupyter lab` starts it up, opens browser window\n\n## AITK Community\n\nFor questions and comments, please use https://github.com/ArtificialIntelligenceToolkit/aitk/discussions/\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "Python tools for AI",
"version": "2.0.1",
"project_urls": {
"Homepage": "https://github.com/ArtificialIntelligenceToolkit/aitk"
},
"split_keywords": [
"ai",
" artificial intelligence",
" robots",
" simulator",
" jupyter",
" python",
" machine learning",
" neural networks",
" keras",
" tensorflow"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "fa54a38f34f61cc52241007760f2dc6a8d8cfcf4b4f475b5c47abb7e28c13fa9",
"md5": "80beaabcc65e56596243470f42dcaa11",
"sha256": "454a6ee39bb8fe139acec48f8cef737399c2837163a2ab25047bfa40848dd27f"
},
"downloads": -1,
"filename": "aitk-2.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "80beaabcc65e56596243470f42dcaa11",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9",
"size": 454165,
"upload_time": "2024-04-01T19:50:59",
"upload_time_iso_8601": "2024-04-01T19:50:59.171395Z",
"url": "https://files.pythonhosted.org/packages/fa/54/a38f34f61cc52241007760f2dc6a8d8cfcf4b4f475b5c47abb7e28c13fa9/aitk-2.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-04-01 19:50:59",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ArtificialIntelligenceToolkit",
"github_project": "aitk",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "aitk"
}
JSON
