#machine-learning

library to quickly export and deploy entire inference pipelines

The self-evolving agentic framework for bioinformatics

Tools for computational pathology

Scientific computing platform on NumPy/SciPy/pandas/matplotlib: linear algebra, stats, optimization, signals, ML, information theory, chaos, Bayes, metaheuristics, geometry and RL.

Опис репозиторію не опубліковано.

Small-scale MLOps library

swarmdo — self-contained AI agent orchestration for Claude Code (swarmdo.com)

Kubernetes-native remote dev environments for AI/ML engineers. Code locally, run on cluster GPUs — live file sync, SSH/tmux into pods, multi-pod PyTorchJob support, and detached job control.

Ferrum is a statistical visualization library for Python: a grammar-first charting system that unifies exploratory plots, statistical graphics, interactive views, and model diagnostics, backed by a Rust engine. Built in 10 days by one human and an agentic Claude framework.

Опис репозиторію не опубліковано.

Extract, transform, load/download and augment images and annotations for object detection, clustering or classification workflows

Common utilities for ONNX converters

DBSCAN, HDBSCAN, and OPTICS clustering algorithms.

A high-performance automatic differentiation library for Rust

Official NPM packages from MeridianAlgo. A professional-grade quantitative finance framework for JavaScript and TypeScript, bringing institutional-grade trading and analysis tools to the Node.js ecosystem.

A Python scikit for building and analyzing recommender systems

ONNX / GoMLX Conversion

Efficient convolution for sparse data on FPGAs

Опис репозиторію не опубліковано.

Machine learning framework written in C.

Local code search for AI agents: six fast, purpose-built tools that return ranked answers, not raw grep. Because maybe grep isn't all you need... 🍬

Ruby wrapper for the Qdrant vector search database API

Regression analysis in Rust.

Python bindings for fdars-core – Functional Data Analysis in Rust

data science in JavaScript, part of the tangent scientific computing suite

Опис репозиторію не опубліковано.

Automated feature engineering for (almost) any dataframe

Julia package of loss functions for machine learning.

Repository for all things around tabular dataset curation for benchmarking!

MLPipelineHolder is a straightforward framework for reproducible machine-learning experimentation in Jupyter notebooks.