ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.
A New Ethical Open Source License for Machine Learning from ml5.js?
I put things here so they are on the internet
jax-js: an ML library for the web
JAX in pure JavaScript, as a flexible machine learning library and compiler.
Machine Learning | Google for Developers
A New Code of Conduct and License for ml5.js
Today we are excited to announce two new parts of ml5.js: a new and improved Code of Conduct and our very own software license.
Machine Learning Glossary | Google for Developers
This glossary defines a wide range of machine learning terms, including those specific to TensorFlow and large language models.
12britz/awesome-free-models
A curated list of free AI models, APIs, and tools you can use without paying a cent.
Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face
Generative artificial intelligence (AI) and machine learning (ML) models are being adopted across a variety of domains. As these technologies develop, there is notable diversity in their levels of availability and paths of diffusion. For example, fully closed-source models may be available through chatbots and API calls, but their weights, source code, training data, and other artifacts remain hidden from view. In contrast, open models make some or all of these materials publicly available for developers and downstream users.
yorkie/tensorflow-nodejs
TensorFlow Node.js provides idiomatic JavaScript language bindings and a high layer API for Node.js users. TensorFlow Node.js provides idiomatic JavaScript language bindings and a high layer API for Node.js users.
Introducing beginners to the mechanics of machine learning – Miriam Posner
Every year, I spend some time introducing students to the mechanics of machine learning with neural nets. I definitely don’t go into great depth; I usually only have one class for this. But I try to unpack at least some of the major concepts, so that ML isn’t quite such a black box.
What is Machine Learning? | IBM
Machine learning is the subset of AI focused on algorithms that analyze and “learn” the patterns of training data in order to make accurate inferences about new data.
Machine Learning Algorithms, Applications: Key Methods, Real-World Uses
Key Takeaways Traditional algorithms such as regression, decision trees, boosting, clustering, and PCA remain highly useful for practical ML problems.Neural net
Web Engines Hackfest 2025
What Are Machine Learning Algorithms? | IBM
A machine learning algorithm is the procedure and mathematical logic through which an AI model learns patterns in training data and applies to them to new data.
