GitHub
dspy
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need...
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
senior-ml-engineer
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
GitHub
senior-prompt-engineer
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
GitHub
analytics-engineer
Expert analytics engineering covering data modeling, dbt development, data transformation, and semantic layer management.
GitHub
data-scientist
Expert data science covering machine learning, statistical modeling, experimentation, predictive analytics, and advanced analytics.
GitHub
ml-ops-engineer
Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation.
GitHub
multi-model-validation
Run multiple AI models in parallel for 3-5x speedup with ENFORCED performance statistics tracking. Use when validating with Grok, Gemini, GPT-5, DeepSeek, or Claudish proxy for code review, consensus analysis,...
GitHub
data-analyst
A data analyst skill that guides Claude through structured, professional data analysis workflows. Use this skill when the user requests data analysis work including analyze, query, dashboard, metrics, EDA, coho...
GitHub
experiment-logger
Log ML experiments with hyperparameters, metrics, and plots; human interprets results and plans next experiments
GitHub
reasoningbank-intelligence
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cogn...
GitHub
agentdb-learning-plugins
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, impleme...
GitHub
flow-nexus-neural
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
GitHub
reasoningbank-with-agentdb
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learnin...
GitHub
ai-services
Configure DigitalOcean Gradient AI serverless inference and Agent Development Kit. Use when adding LLM inference, model access keys, serverless AI endpoints, or building AI agents with ADK on App Platform.
GitHub
foundation-models
Apple Foundation Models framework for on-device AI, @Generable macro, guided generation, tool calling, and streaming. Use when user asks about on-device AI, Apple Intelligence, Foundation Models, @Generable, LL...
GitHub
powergraph-gnn-research
Research pipeline for topology-aware GNN representation learning on power grids using the PowerGraph benchmark. Use when (1) building physics-guided GNNs for power flow (PF), optimal power flow (OPF), or cascad...
GitHub
mechinterp-decoder
Analyze SAE decoder weights - output influence, feature importance, and decoder similarity
GitHub
mechinterp-validation-suite
Run credibility checks on feature interpretations including split-half stability and shuffle null tests
GitHub
mechinterp-runner
Execute mechanistic interpretability experiments from JSON specs - family sweeps, itemsets, interactions, minimal cores, validation
GitHub
using-spacy-nlp
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when "installing spaCy", "selecting model for nlp" (en_core_web_sm/md/lg/trf), "tokenization", "POS tagging", "name...
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
ml-monitoring
Production-grade ML model monitoring, drift detection, and observability
GitHub
model-serving
Master model serving - inference optimization, scaling, deployment, edge serving
GitHub
experiment-tracking
Master ML experiment tracking - MLflow, W&B, Neptune, versioning, reproducibility
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.