Cloud Native Batch System (Project under CNCF).
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Works with speech, voice, music or other audio using machine-learning models.
CAMEL-AI is an open-source community for finding the scaling laws of agents for data generation, world simulation, task automation.
Creates, rewrites or summarizes written content with language models.
Works with speech, voice, music or other audio using machine-learning models.
An implementation of Dell Zhang's solution to Wikipedia's Participation Challenge on Kaggle.
Works with speech, voice, music or other audio using machine-learning models.
Tokenizers for Natural Language Processing in Julia.
Word Embeddings: the full implementation of word2vec, GloVe in Go.
A Julia package for Princeton's WordNet.
An Autonomous LLM Agent for Complex Task Solving.
Works with speech, voice, music or other audio using machine-learning models.
Light-weight, universal resource scheduler for container orchestrator systems.
Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.
Andegraf Rockets is an educational resource for documentaries, courses, books, reference material, or self-learning.
Earth and Moon Viewer is an educational resource for documentaries, courses, books, reference material, or self-learning.
Lost and Found Nature is an educational resource for documentaries, courses, books, reference material, or self-learning.
WebGL and GLSL Workshop provides educational videos, lessons, tutorials, or self-learning resources.
World Births and Deaths is an educational resource for documentaries, courses, books, reference material, or self-learning.
Educational audio and video directory for lectures, courses, audiobooks, and learning resources.
Documentary Network is an educational video or documentary resource for learning from films and non-fiction media.
Open-source project that provides AI-assisted learning, courses, tutorials, or study support.
Neural networks, regression and feature learning in Clojure.
Course materials and notes for Stanford class CS231n: Deep Learning for Computer Vision.