github.com
Ultralytics' YOLOv8 implementation with C++ support for real-time object detection and tracking, optimized for edge devices.
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github.com
Light-weight, universal resource scheduler for container orchestrator systems.
github.com
Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.
github.com
A Python module for metric learning.
github.com
Metric Learning Algorithms in Python.
spinningup.openai.com
An educational resource designed to let anyone learn to become a skilled practitioner in deep reinforcement learning.
learning.google.com
Learn About provides AI-assisted learning, courses, tutorials, or study support.
ufldl.stanford.edu
UFLDL provides AI-assisted learning, courses, tutorials, or study support.
github.com
A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.
github.com
Roadmap to becoming an Artificial Intelligence Expert.
aistudentpack.com
A new upcoming pack focused on providing students with the essential AI tools for their education. Currently on a waitlist.
github.com
Code for Data Science at Olin College, Spring 2014.
animatedai.github.io
Animations and instructional videos about neural networks.
chromewebstore.google.com
Anki Export provides AI-assisted learning, courses, tutorials, or study support.
github.com
Approximate nearest neighbours implementation.
github.com
Curated list of federated learning publications, re-organized from Arxiv (mostly).
github.com
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
github.com
Neural networks in JavaScript - continued community fork of Brain.
github.com
Fast, flexible and fun neural networks. This is the successor of PyBrain.
buildclub.ai
Build with AI, together. Anyone can AI, so get started today.
github.com
Implementation of Random Forest in Common Lisp.
github.com
Multidimensional cluster generation in Julia.
github.com
Multidimensional cluster generation in R.
github.com
Basic functions for clustering data: k-means, dp-means, etc.