#machine-learning

Lightweight plotting to the terminal. 4x resolution via Unicode.

Complete python SDK, CLI, and API reference for integrating with the Pictograph.io platform.

Опис репозиторію не опубліковано.

Gradient Boosting library with KAN (Kolmogorov-Arnold Network) learners

Variable Importance Plots (VIPs)

🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.

Parallel Barnes-Hut t-SNE implementation written in Rust.

Google Gemini MCP - Use Google's visual, video and chat capabilities in your AI Assistant. Uses MCP Apps to preview created images, landing pages, SVGs and video

optical attention via wave interference in holographic crystals verified to float precision. the math is done. contribute to build the hardware.star it, fork it, break it.

JavaScript client for txtai

Build flexible hierarchical multi-instance learning models.

Crystallize is a lightweight Python framework for rigorous, reproducible data science experiments. Define modular pipelines, apply treatments as experimental variations, and verify hypotheses with statistical tests, all with built-in caching, immutability, and parallelism for trustworthy, efficient results.

Python SDK for Aetherfy Vectors — a drop-in replacement for qdrant-client with global sub-50ms latency, built-in analytics, workspace scoping, and client-side payload schema validation.

Опис репозиторію не опубліковано.

Data sets used in the book, gallery, or in examples of mlr3.

Read huggingface.co as data: every model, dataset, space, user, org, collection and paper as a typed record with an hf:// URI and a knowledge graph of the edges between them

Python tools for text to speech (TTS), speech to text (STT), and speech to speech (STS) powered by MLX

Large file storage for Git via symlinks - no LFS server, no pointer files, any rclone remote

High performance gradient boosting for Ruby

IbisML is a library for building scalable ML pipelines using Ibis.

Automatic Generation of Interactive Visualizations for Statistical Results

A nvImageCodec library of GPU- and CPU- accelerated codecs featuring a unified interface

Predicting time-consuming CQL queries in language corpora

Fast dataset format and loader

:us: a python library for parsing unstructured United States address strings into address components

Опис репозиторію не опубліковано.

Zero-config nonparametric supervised learning for Rust

Fetch The Gradient AI research publication posts and listings from the terminal