Curated list of federated learning publications, re-organized from Arxiv (mostly).
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Curated list of ML related resources for Ruby.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Beam provides machine-learning models, research, training resources, or evaluation tools.
Benchmarking Hallucination Detection Methods in RAG Towards Data Science provides machine-learning models, research, training resources, or…
CPU and GPU-accelerated Machine Learning Library.
BigModel provides machine-learning models, research, training resources, or evaluation tools.
Blackbox AI provides machine-learning models, research, training resources, or evaluation tools.
Blog provides machine-learning models, research, training resources, or evaluation tools.
Neural networks in JavaScript - continued community fork of Brain.
Fast, flexible and fun neural networks. This is the successor of PyBrain.
Build with AI, together. Anyone can AI, so get started today.
Butternut AI provides machine-learning models, research, training resources, or evaluation tools.
Fast open framework for deep learning.
Cal.ai provides machine-learning models, research, training resources, or evaluation tools.
Torch-like deep learning framework for Javascript with support for tensors, autograd, optimizers, and other neural net constructs.
Interactive Hugging Face app that shares a machine-learning model, framework, demonstration or technical resource.
Chain of Thought provides machine-learning models, research, training resources, or evaluation tools.
Charisma provides machine-learning models, research, training resources, or evaluation tools.
ChatGPT, DALL-E 2 and the collapse of the creative process provides machine-learning models, research, training resources, or evaluation tools.
ChessArena provides machine-learning models, research, training resources, or evaluation tools.
Implementation of Random Forest in Common Lisp.
Python library for data-centric AI and machine learning with messy, real-world data and labels.
Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.