Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: artificial

英語版ディレクトリ

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
信頼
カテゴリ: design-creative監査

WPPConnect is an open source project developed by the JavaScript community with the aim of exporting functions from WhatsApp Web to the node, which can be used to support the creation of any interaction, such as customer service, media sending, intelligence recognition based on phrases artificial and many other things, use your imagination

3.4K
Stars
76/100
信頼
カテゴリ: browser-automation監査

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp.

6.6K
Stars
84/100
信頼
カテゴリ: browser-automation監査

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
信頼
カテゴリ: ml-automation監査

Roadmap to becoming an Artificial Intelligence Expert in 2022

31K
Stars
76/100
信頼
カテゴリ: data-analysis監査

GeoAI: Artificial Intelligence for Geospatial Data

3.1K
Stars
80/100
信頼
カテゴリ: geo-science監査

Become skilled in Artificial Intelligence, Machine Learning, Generative AI, Deep Learning, Data Science, Natural Language Processing, Reinforcement Learning and more with this complete 0 to 100 repository.

4.1K
Stars
80/100
信頼
カテゴリ: ml-automation監査

Artificial Intelligence Infrastructure-as-Code Generator.

3.8K
Stars
76/100
信頼
カテゴリ: devops監査

Maid is a free and open source application for interfacing with llama.cpp models locally, and with Anthropic, DeepSeek, Ollama, Mistral and OpenAI models remotely.

2.5K
Stars
83/100
信頼
カテゴリ: support-automation監査

人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

13K
Stars
71/100
信頼
カテゴリ: data-analysis監査

A curated list of Artificial Intelligence Top Tools

5.5K
Stars
76/100
信頼
カテゴリ: agent-frameworks監査

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2026 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

5.3K
Stars
83/100
信頼
カテゴリ: ml-automation監査