AIxDESIGN Bookmark Library

AIxDESIGN Bookmark Library

2056 bookmarks
Custom sorting
ML Art Colabs
ML Art Colabs
by dvschultz | A list of cool Colabs on Machine Learning Imagemaking or other artistic purposes
·github.com·
ML Art Colabs
Everyday Experiments — Neverending Catalogue
Everyday Experiments — Neverending Catalogue
Neverending Catalogue is a technical prototype which would create computer-generated bedrooms to act as an inspiration database, essentially taking on the role of an interior designer for you to consult at your leisure.
·everydayexperiments.com·
Everyday Experiments — Neverending Catalogue
Intro to AI for Architectural Design Explorations
Intro to AI for Architectural Design Explorations
From Engineering ArchiTECHture | An exploration into how AI is used in architectural design hosted by AIxDesign member Mayur (who hosts amazing sessions like this on regular basis)!
·youtube.com·
Intro to AI for Architectural Design Explorations
Generative Engine | RunwayML Experiments
Generative Engine | RunwayML Experiments
A storytelling machine that automatically generates synthetic images as you write new words and sentences. Made with RunwayML
·experiments.runwayml.com·
Generative Engine | RunwayML Experiments
dvschultz/dataset-tools
dvschultz/dataset-tools
Tools for quickly normalizing image datasets. Contribute to dvschultz/dataset-tools development by creating an account on GitHub.
·github.com·
dvschultz/dataset-tools
Paper Kingdom
Paper Kingdom
Digital collages based on public domain scientific illustrations of plants and animals from the Biodiversity Heritage Library.
·paperkingdom.brianfoo.com·
Paper Kingdom
Anatomies of Intelligence
Anatomies of Intelligence
An artistic research initiative seeking to make connections between the formats and collections of anatomical knowledge and investigations into the “anatomy” of computational learning and prediction processes, datasets and machine learning models by Joana Chicau and Jonathan Reus.
·anatomiesofintelligence.github.io·
Anatomies of Intelligence
Should AI Models Be Explainable? That depends.
Should AI Models Be Explainable? That depends.
By Katherine Miller | A Stanford researcher advocates for clarity about the different types of interpretability and the contexts in which it is useful.
·hai.stanford.edu·
Should AI Models Be Explainable? That depends.
Together
Together
We call for collaborative practitioners in art, design and technology to explore Artificial Intelligence (AI) & Machine Learning (ML), data & networks.
·befantastic.in·
Together
Head of Design - Learn @ Datacamp
Head of Design - Learn @ Datacamp
The days of learning data science by passively consuming video lectures are over. Real learning takes place when a student’s hands are on the keyboard, writing code, working with data, and solving problems. If you agree, keep reading!
·boards.greenhouse.io·
Head of Design - Learn @ Datacamp
Predominantly
Predominantly
Explore album covers by their color schemes
·predominant.ly·
Predominantly
Recognition
Recognition
Recognition was an artificial intelligence program that compares up-to-the-minute photojournalism with British art from the Tate collection.
·recognition.tate.org.uk·
Recognition
MIMIC Project for Creative Machine Learning
MIMIC Project for Creative Machine Learning
The mimic project offers a way to make new kinds of music, sound and creative arts experiences using machine learning, machine listening and artificial intelligence.
·mimicproject.com·
MIMIC Project for Creative Machine Learning
Gradient - ML Showcase
Gradient - ML Showcase
A collection of interactive Machine Learning projects curated by Paperspace Gradient.
·ml-showcase.paperspace.com·
Gradient - ML Showcase
trekhleb/machine-learning-experiments
trekhleb/machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo - trekhleb/machine-learning-experiments
·github.com·
trekhleb/machine-learning-experiments
bwang514/awesome-HAI
bwang514/awesome-HAI
A curated list of awesome Human-AI Interaction. Contribute to bwang514/awesome-HAI development by creating an account on GitHub.
·github.com·
bwang514/awesome-HAI
alsino/creative-applications-ml
alsino/creative-applications-ml
All code and materials for the DAAD introductory workshop on machine learning - alsino/creative-applications-ml
·github.com·
alsino/creative-applications-ml
yining1023/machine-learning-for-the-web
yining1023/machine-learning-for-the-web
Repository for the "Machine Learning for the Web" class at ITP, NYU - yining1023/machine-learning-for-the-web
·github.com·
yining1023/machine-learning-for-the-web
Learn Artificial Neural Networks on Brilliant
Learn Artificial Neural Networks on Brilliant
This interactive course dives into the fundamentals of artificial neural networks, from the basic frameworks to more modern techniques like adversarial models. You’ll answer questions such as how a computer can distinguish between pictures of dogs and cats, and how it can learn to play great chess. Using inspiration from the human brain and some linear algebra, you’ll gain an intuition for why these models work – not just a collection of formulas. This course is ideal for students and professionals seeking a fundamental understanding of neural networks, or brushing up on basics.
·brilliant.org·
Learn Artificial Neural Networks on Brilliant