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: algorithm-competitions

英語版ディレクトリ

🌟100+ 原创 LLM / RL 原理图📚,《大模型算法》作者巨献!💥(100+ LLM/RL Algorithm Maps )

4.5K
Stars
74/100
信頼
カテゴリ: ml-automation監査

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

2.2K
Stars
85/100
信頼
カテゴリ: ml-automation監査

This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.

1.6K
Stars
84/100
信頼
カテゴリ: rag-knowledge監査

Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.

1.3K
Stars
79/100
信頼
カテゴリ: finance監査

A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm

4.0K
Stars
83/100
信頼
カテゴリ: ml-automation監査

数学建模竞赛(CUMCM/MCM/电工杯)的Agent工作流,支持Claude Code和Codex CLI,提供10阶段流程、决策日志和可恢复协作。

153
Stars
71/100
信頼
カテゴリ: research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

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

10K
Stars
72/100
信頼
カテゴリ: ml-automation監査

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

34K
Stars
80/100
信頼
カテゴリ: research監査

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

34K
Stars
77/100
信頼
カテゴリ: data-analysis監査

🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

2.7K
Stars
76/100
信頼
カテゴリ: rag-knowledge監査

A Python implementation of LightFM, a hybrid recommendation algorithm.

5.1K
Stars
71/100
信頼
カテゴリ: ml-automation監査