GitHub
google-adk-python
Build AI agents with Google's Agent Development Kit (ADK) Python. Use when building AI agents with tool integration, multi-agent systems, workflow agents (sequential, parallel, loop), or deploying to Vertex AI.
Skills IA tools machine learning
Découvrez les skills tools machine learning, comparez leurs dépôts et consultez leurs instructions.
Catégories: tools machine learning
tools machine learning Effacer les filtres
Explorer
GitHub
huggingface-js
Runs ML models in the browser and Node.js with Transformers.js and Hugging Face Inference API. Use when adding local inference, embeddings, or calling hosted models without GPU servers.
GitHub
replicate
Runs open-source ML models via Replicate API for image generation, LLMs, and audio. Use when calling Stable Diffusion, Llama, Whisper, or other models without infrastructure management.
GitHub
agent-detector
CRITICAL: MUST run for EVERY message. Detects agent, complexity, AND model automatically. Always runs FIRST.
GitHub
pytorch-lightning
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed train...
GitHub
pyhealth
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical predi...
GitHub
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), buil...
GitHub
scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparamet...
GitHub
hypogenic
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis)....
GitHub
scikit-survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox mo...
GitHub
stable-baselines3
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations....
GitHub
pymc
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
GitHub
statsmodels
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous...
GitHub
pufferlib
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (At...
GitHub
aeon
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 temp...
GitHub
torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
GitHub
modal
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU...
GitHub
shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (wate...
GitHub
transformers
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answeri...
GitHub
using-the-force
Comprehensive guide for using The Force MCP server - a unified interface to 11 AI models (OpenAI, Google, Anthropic, xAI) with intelligent context management, project memory, and multi-model collaboration. This...
GitHub
convex-development
Apply Convex database best practices for cost optimization, performance, security, and architecture. Use when: building Convex backends, optimizing queries, handling embeddings/vector search, reviewing Convex c...
GitHub
healthbench-evaluation
Run HealthBench Hard benchmark evaluation using multi-specialist council architecture with deterministic safety stack.
GitHub
fine-tune
Use when you need to fine-tune(ファインチューニング) and optimize LangGraph applications based on evaluation criteria. This skill performs iterative prompt optimization for LangGraph nodes without changing the...
GitHub
knowledge-manager
Manages user preferences and learned knowledge with confidence scoring
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.