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: genetic-algorithm

Annuaire en anglais

🌟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
Confiance
Catégorie: ml-automationAudit

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
Confiance
Catégorie: ml-automationAudit

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
Confiance
Catégorie: rag-knowledgeAudit

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

1.3K
Stars
79/100
Confiance
Catégorie: financeAudit

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

10K
Stars
84/100
Confiance
Catégorie: ml-automationAudit

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

4.0K
Stars
83/100
Confiance
Catégorie: ml-automationAudit

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

3.7K
Stars
80/100
Confiance
Catégorie: ml-automationAudit

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
Confiance
Catégorie: data-analysisAudit

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
Confiance
Catégorie: researchAudit

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
Confiance
Catégorie: data-analysisAudit

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

2.7K
Stars
76/100
Confiance
Catégorie: rag-knowledgeAudit

Genetic Programming in Python, with a scikit-learn inspired API

1.9K
Stars
73/100
Confiance
Catégorie: ml-automationAudit