Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

robuststl



robuststl

AIMA exercises is an interactive and collaborative platform for digitalizing the exercises of the book Artificial Intelligence: A Modern Approach by Stuart J. Russell and Peter Norvig.
Exercises for the book Artificial Intelligence: A Modern Approach. The idea is that in the fourth edition of the book, exercises will be online only (they will not appear in the book). This site will showcase the exercises, and will be a platform for students and teachers to add new exercises.
The present version of AIMA-Exercises uses Jekyll 3 and Ruby 2.5. To run the project locally:

  1. Install a full Ruby development environment
  2. Install Jekyll and bundler gems
  3. Installation Guides:
  1. Clone the project locally.
  2. Go to the folder directory where you cloned the project in the terminal.
  3. gem install Jekyll bundler
  4. bundle exec Jekyll serve

About the tool


Tool type(s):


Objective(s):



Country of origin:



Type of approach:






Programming languages:



Github stars:

  • 252

Github forks:

  • 53

Modify this tool

Use Cases

There is no use cases for this tool yet.

Would you like to submit a use case for this tool?

If you have used this tool, we would love to know more about your experience.

Add use case
catalogue Logos

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.