majiayu000/claude-skill-registry - 35ページ

model-convergence-forecast

Forecast convergence patterns in multi-model consensus scenarios.

原文の言語: 英語

model-evaluation-benchmark

Automated reproduction of comprehensive model evaluation benchmarks following the Benchmark Suite V3. Auto-activates for model benchmarking, comparison evaluation, or performance testing between AI models.

原文の言語: 英語

my-ml-project

Managing ML experiments, metrics, parameters, and artifacts using MLflow, Weights & Biases, and best practices for reproducible ML experiments and model versioning.

原文の言語: 英語

explainability

See the main Model Explainability skill for comprehensive XAI coverage.

原文の言語: 英語

model-explainer

Model interpretability and explainability using SHAP, LIME, feature importance, and partial dependence plots. Activates for "explain model", "model interpretability", "SHAP", "LIME", "feature importance", "why prediction", "model explanation". Generates…

原文の言語: 英語

model-interpretability

Interpret ML model predictions using SHAP, LIME, attention visualization, and probing techniques. Use when explaining model decisions, debugging model behavior, or building trust in ML systems.

原文の言語: 英語

model-optimization

Comprehensive guide for ML model optimization techniques including quantization, pruning, knowledge distillation, and inference optimization.

原文の言語: 英語

ai-model-registry

Centralized management of machine learning models throughout their lifecycle, including versioning, metadata, and production deployment.

原文の言語: 英語

model-registry

Centralized model versioning, staging, and lifecycle management. Activates for "model registry", "model versioning", "model staging", "deploy to production", "rollback model", "model metadata", "model lineage", "promote model", "model catalog". Manages ML…

原文の言語: 英語

model-risk-management

Model Risk Management (MRM) is a framework designed to manage the risk of adverse consequences resulting from decisions based on incorrect or misused model outputs. While software engineering focuses

原文の言語: 英語

model-serving-inference

Model serving is the process of deploying ML models to production and handling inference requests efficiently at scale.

原文の言語: 英語

model-serving-kubernetes

Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.

原文の言語: 英語

model-training

Model training is the process of teaching machine learning models to make predictions or decisions based on data. This skill covers comprehensive training workflows including pipeline design, data pre

原文の言語: 英語

model-versioning

Model versioning is practice of tracking and managing different versions of machine learning models throughout their lifecycle. This skill covers versioning strategies, model registries, metadata mana

原文の言語: 英語

multimodal-medical-imaging

Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.

原文の言語: 英語

multimodal-ml

Vision-language model patterns including CLIP, LLaVA, cross-modal alignment, and embedding fusion. Use when building or integrating multimodal ML systems.

原文の言語: 英語

multimodal-rag

CLIP, SigLIP 2, Voyage multimodal-3 patterns for image+text retrieval, cross-modal search, and multimodal document chunking. Use when building RAG with images, implementing visual search, or hybrid retrieval.

原文の言語: 英語

musik-app-bei

Datenbankrecht für Musik-, Film- und Bildarchive: §§ 87a-87e UrhG für Mediendatenbanken, Schichtenschutz (Datenbankherstellerrecht + Urheberrecht an Einzelwerken), Lizenzmodelle für Stock-Media-Portale und Verwertungsgesellschaften (GEMA, VGBild),…

原文の言語: ドイツ語

nano-banana-pro

Generate or edit images via Gemini 3 Pro Image (Nano Banana Pro).

原文の言語: 英語

nano-banana-pro

Generate or edit images via Gemini 3 Pro Image (Nano Banana Pro). RoastPlusでの用途: コーヒー豆の視覚化、焙煎度合いの比較画像、クイズ用の画像生成、設定画面のアイコン作成等。

原文の言語: 複数言語

nano-banana-pro

Gere ou edite imagens via Gemini 3 Pro Image (Nano Banana Pro).

原文の言語: 英語

nano-banana-pro

Generate or edit images via Gemini 3 Pro Image (Nano Banana Pro).

原文の言語: 英語

nanobanana

StudioJinsei用Nanobanana画像生成Skill。Google Gemini APIを使用してロゴ、コトネちゃん、サイトビジュアル等を生成します。

gemini-image-generator

Generate images using Google Gemini NanoBanana via browser automation. Use this skill for general-purpose AI image generation from text prompts. Includes persistent authentication, automatic environment setup, and reference image support for style matching.

原文の言語: 英語

nanobanana-prompts

NanoBanana（Google Gemini画像生成）向けの高品質プロンプトを生成。画像生成、編集、フェイススワップ、背景変更、キャラクター一貫性のプロンプト作成を支援。

neuropixels-analysis

Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when…

原文の言語: 英語

new-sdg

Implement a new synthetic data generator using NeMo Data Designer by defining its configuration and executing a preview job.

原文の言語: 英語

nixtla-anomaly-detector

Detects anomalies in time series data using TimeGPT. Identifies outliers, level shifts, and trend breaks without model training. Use when identifying anomalies, outliers, or unusual patterns in time series. Trigger with "detect anomalies", "find outliers",…

原文の言語: 英語

nixtla-batch-forecaster

Forecast multiple time series in parallel using TimeGPT. Use when processing 10-100+ contracts efficiently. Trigger with 'batch forecast' or 'parallel forecasting'.

原文の言語: 英語

nixtla-cross-validator

Performs rigorous time series cross-validation using expanding and sliding windows. Use when needing to evaluate the performance of time series models on unseen data. Trigger with cross validate time series, evaluate forecasting model, time series backtesting.

原文の言語: 英語

nixtla-liquidity-forecaster

Forecasts orderbook depth and spreads to optimize trade execution timing. Use when needing to estimate market liquidity for large orders. Trigger with 'forecast liquidity', 'predict orderbook', 'estimate depth'.

原文の言語: 英語

nixtla-model-selector

Automatically selects the best forecasting model between StatsForecast and TimeGPT based on time series data characteristics. Use when unsure which model performs best. Trigger with 'auto-select model', 'choose best model', 'model selection'.

原文の言語: 英語

nixtla-timegpt-finetune-lab

Configure TimeGPT fine-tuning on custom datasets with Nixtla SDK. Use when training domain-specific forecast models. Trigger with 'fine-tune TimeGPT' or 'train custom model'.

原文の言語: 英語

nixtla-timegpt-lab

Provides expert Nixtla forecasting using TimeGPT, StatsForecast, and MLForecast. Generates time series forecasts, analyzes trends, compares models, performs cross-validation, and recommends best practices. Activates when user needs forecasting, time series…

原文の言語: 英語

nlp-pipeline-builder

Natural language processing ML pipelines for text classification, NER, sentiment analysis, text generation, and embeddings. Activates for "nlp", "text classification", "sentiment analysis", "named entity recognition", "BERT", "transformers", "text…

原文の言語: 英語

nlp-processing

Process and analyze natural language using modern NLP techniques. Use for text classification, named entity recognition, sentiment analysis, tokenization, embeddings, transformers (BERT, GPT), and language understanding tasks.

原文の言語: 英語

nnsight-basics

Core nnsight concepts for neural network interpretability. Use when setting up models, tracing activations, saving values, or making basic interventions on model internals.

原文の言語: 英語

bio-metabolomics-normalization-qc

Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.

原文の言語: 英語

numpy-core

Fundamental NumPy operations including ndarray creation, dtypes, shape manipulation, and basic operations with a focus on memory alignment and data views. Triggers: numpy, ndarray, dtype, reshape, memory alignment, array-creation.

原文の言語: 英語

numpy-fft

Discrete Fourier Transform routines for spectral analysis, signal filtering, and frequency-domain operations. Triggers: fft, fourier transform, spectral analysis, rfft, fftshift, ifft.

原文の言語: 英語