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tools machine learning AI 技能

发现 tools machine learning 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。

分类目录: tools machine learning

显示第 1,105–1,128 个,共 1,317 个

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GitHub

bias-assessment

DTMC-marketplace

Evaluate AI systems for fairness using demographic parity, equalized odds, and bias detection techniques with mitigation strategies.

GitHub

model-selection

DTMC-marketplace

Select appropriate AI/ML models based on capability matching, benchmarks, cost-performance tradeoffs, and deployment constraints.

GitHub

explainability-planning

DTMC-marketplace

Plan explainable AI (XAI) requirements including SHAP, LIME, attention visualization, and regulatory explainability needs.

GitHub

token-budgeting

DTMC-marketplace

Estimate and optimize AI/ML costs including token usage, context window management, batch processing, and caching strategies.

GitHub

hitl-design

DTMC-marketplace

Design human-in-the-loop workflows including review queues, escalation patterns, feedback loops, and quality assurance for AI systems.

GitHub

kaggle-api-expert

sweeden-ttu

Expert agent for Kaggle API authentication, dataset management, and running Kaggle notebooks on Texas Tech HPCC. Specializes in connecting Jupyter notebooks to Kaggle API and submitting to code competitions. Al...

GitHub

reasoningbank-intelligence

adebold

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

reasoningbank-with-agentdb

adebold

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

agentdb-learning-plugins

adebold

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

behavioral-modes

seanpham99

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

GitHub

llm-evaluation

ccf

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing...

GitHub

embedding-strategies

ccf

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

GitHub

gcp-deploy

mapachekurt

Skill for deploying and managing agents on Google Cloud Platform, specifically Vertex AI Reasoning Engine.

GitHub

training-apo-agents

asvskartheek

Train LangChain/LangGraph agents using Microsoft Agent-Lightning APO (Automatic Prompt Optimization). Use when user mentions APO training, prompt optimization, agent-lightning, training multi-agent systems, tra...

GitHub

ai-integration

Monsoft-Solutions

Guide AI feature development using @monsoft/ai package with Langfuse telemetry. Use when building AI-powered features, text generation, or structured outputs.

GitHub

gokart

inakam

M3社が開発したPythonの機械学習パイプラインツールgokartに関する深い知識とベストプラクティスを提供する。Use when reviewing gokart task designs, implementing type-safe ML pipelines, writing gokart tests, or workin...

GitHub

openrouter

rawwerks

Use this skill when the user wants to call different LLM models through OpenRouter's unified API, compare model responses, track costs and response times, or find the best model for a task. Triggers include req...

GitHub

jax

yonesuke

Essential tools for using JAX in machine learning and mathematical analysis, covering core concepts, transformations, ML specifics, control flow, and parallelism.

GitHub

developing-flax-models

yonesuke

A comprehensive guide for developing, training, and managing neural networks using Flax NNX. Use when defining models, managing state, or writing training loops.

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