Skip to main content

Python tools for AI

Project description

aitk: Artificial Intelligence Toolkit

DOI

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

Computational Essays

Each computational essay is described at Computational Essays. Our computational essays and a suggested sequencing through the notebooks can be found in the notebooks folder of this repo.

Artifical Intelligence Toolkit

aitk is a Python package containing the following modules.

AITK Community

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

aitk-3.0.0b1-py3-none-any.whl (454.8 kB view details)

Uploaded Python 3

File details

Details for the file aitk-3.0.0b1-py3-none-any.whl.

File metadata

  • Download URL: aitk-3.0.0b1-py3-none-any.whl
  • Upload date:
  • Size: 454.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for aitk-3.0.0b1-py3-none-any.whl
Algorithm Hash digest
SHA256 4d4c9423c69a4aff3c1b75a058e0288b09885cbe374e572569a605078328e8f3
MD5 476867bcd31940f5fc8ef03e08a63025
BLAKE2b-256 d909ea13ca574e7831fa67cbd486366e7120bad752cb6f2e8d698c7afdb329e1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page