Directorio de skills

Descubre skills reutilizables para AI agents.

Busca skills reales de GitHub por tarea y revisa stars, confianza, auditoría, categoría y ruta de instalación antes de utilizarlos.

Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.

Resultados de búsqueda: prediction

Directorio en inglés

Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.

54K
Stars
83/100
Confianza
Categoría: researchAuditoría

Message Passing Neural Networks for Molecule Property Prediction

2.4K
Stars
74/100
Confianza
Categoría: ml-automationAuditoría

MiroThinker is a deep research agent optimized for complex research and prediction tasks. Our latest models, MiroThinker-1.7, achieves 74.0 and 75.3 on the BrowseComp and BrowseComp Zh, respectively.

8.3K
Stars
84/100
Confianza
Categoría: researchAuditoría

CCXT for prediction markets. PMXT is a unified API for trading on Polymarket, Kalshi, and more.

2.0K
Stars
77/100
Confianza
Categoría: financeAuditoría

Natural Gradient Boosting for Probabilistic Prediction

1.9K
Stars
80/100
Confianza
Categoría: ml-automationAuditoría
VAR83

[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

8.7K
Stars
83/100
Confianza
Categoría: media-automationAuditoría

Offline multi-agent simulation & prediction engine. English fork of MiroFish with Neo4j + Ollama local stack.

2.3K
Stars
83/100
Confianza
Categoría: agent-frameworksAuditoría

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
Confianza
Categoría: researchAuditoría

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.

25K
Stars
77/100
Confianza
Categoría: design-creativeAuditoría

Lightweight, useful implementation of conformal prediction on real data.

1.1K
Stars
74/100
Confianza
Categoría: robotics-iotAuditoría

:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

2.3K
Stars
68/100
Confianza
Categoría: financeAuditoría