Curate and annotate vision, audio, and LLM datasets, track experiments, and manage models on a single platform.
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Data Science at Home is a podcast about machine learning, artificial intelligence, and algorithms.
Data Skeptic is a podcast hosted by Kyle Polich, featuring interviews with experts on data science, machine learning, AI, and statistics.
DD-WRT provides Linux, macOS, BSD, or Unix documentation, tutorials, manuals, and learning guides.
Docs provides Linux, macOS, BSD, or Unix documentation, tutorials, manuals, and learning guides.
Docs provides Linux, macOS, BSD, or Unix documentation, tutorials, manuals, and learning guides.
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
Edge Impulse is the development platform for machine learning on edge devices.
Extension Guide provides Linux, macOS, BSD, or Unix documentation, tutorials, manuals, and learning guides.
Making neural nets uncool again, focused on making deep learning more accessible.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features.
Federated Learning - The Production AI Platform for Federated Learning at Scale.
The elegant machine learning library.
FutureTools supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A research project exploring the role of machine learning in the process of creating art and music.
Greg (Grzegorz) Surma - Portfolio; Machine Learning, Computer Vision, Self-Driving Cars, AI.
Weights & Biases, developer tools for machine learning.
Linux learning site with guides, commands, tutorials, and practical system administration notes.
Hugging Face supports machine learning models, deployment, inspection, datasets, or AI development workflows.
A machine learning craftsmanship blog.
International Conference on Machine Learning.
Illusion Diffusion supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Helps teams build, deploy, observe or operate machine-learning systems.
IUMB supports machine learning models, deployment, inspection, datasets, or AI development workflows.