Annuaire de skills

Découvrez des skills réutilisables pour les AI agents.

Recherchez de vrais skills GitHub par tâche et vérifiez Stars, confiance, audit, catégorie et chemin d’installation avant de les utiliser.

Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.

Résultats de recherche: techniques

Annuaire en anglais

Techniques for deep learning with satellite & aerial imagery

10K
Stars
82/100
Confiance
Catégorie: ml-automationAudit

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

28K
Stars
78/100
Confiance
Catégorie: rag-knowledgeAudit

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

23K
Stars
79/100
Confiance
Catégorie: agent-frameworksAudit

A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.

9.5K
Stars
76/100
Confiance
Catégorie: ml-automationAudit

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

7.6K
Stars
77/100
Confiance
Catégorie: ml-automationAudit

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

1.8K
Stars
77/100
Confiance
Catégorie: developmentAudit

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
Confiance
Catégorie: ml-automationAudit

Tools and Techniques for Blue Team / Incident Response

4.3K
Stars
74/100
Confiance
Catégorie: devopsAudit

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

2.6K
Stars
75/100
Confiance
Catégorie: ml-automationAudit

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

8.7K
Stars
76/100
Confiance
Catégorie: ml-automationAudit

Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.

2.8K
Stars
83/100
Confiance
Catégorie: developmentAudit

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
Confiance
Catégorie: ml-automationAudit