Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: causal-graphs

영문 디렉토리

A tool that converts codebases, SQL schemas, and other files into queryable knowledge graphs for AI coding assistants.

92K
Stars
80/100
신뢰
카테고리: development감사

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

30K
Stars
87/100
신뢰
카테고리: rag-knowledge감사

Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

75K
Stars
84/100
신뢰
카테고리: rag-knowledge감사

✨ Innovative and open-source visualization application that transforms various data formats, such as JSON, YAML, XML and CSV into interactive graphs.

44K
Stars
86/100
신뢰
카테고리: data-analysis감사

Build Real-Time Knowledge Graphs for AI Agents

28K
Stars
82/100
신뢰
카테고리: data감사

A JavaScript library aimed at visualizing graphs of thousands of nodes and edges

12K
Stars
87/100
신뢰
카테고리: data-analysis감사

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

8.2K
Stars
86/100
신뢰
카테고리: ml-automation감사

Uplift modeling and causal inference with machine learning algorithms

5.9K
Stars
76/100
신뢰
카테고리: ml-automation감사

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

4.7K
Stars
76/100
신뢰
카테고리: ml-automation감사

Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

2.8K
Stars
73/100
신뢰
카테고리: agent-frameworks감사

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

2.5K
Stars
83/100
신뢰
카테고리: data-analysis감사

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

2.2K
Stars
85/100
신뢰
카테고리: rag-knowledge감사