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Machine Learning

Training models and neural networks.

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machine-learning
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managing-cache-and-optimization

Use when managing Shannon CLI performance and costs - check cache statistics, clear stale entries, set budgets, understand automatic model selection and cost optimization

krzemienski
krzemienski
data-ai
open
machine-learning
1

plan-mode-arc-gsm8k-improvement

AEGISモデルのARC-Challenge評価改善とGSM8K健全性チェックのためのPlanモード。タイムアウト率・抽出失敗率分析、頑健な回答抽出、データ汚染検査、複数seed評価を実行。

zapabob
zapabob
data-ai
open
machine-learning
1

zrl-parameter-optimizer

This skill should be used when optimizing strategy parameters through grid search, random search, or Bayesian optimization. It provides systematic approaches to find optimal parameter combinations while avoiding overfitting through cross-validation and walk-forward methods.

JeanBaissari
JeanBaissari
data-ai
open
machine-learning
1

ml-systems

Machine Learning Systems - comprehensive knowledge for building production ML systems from data engineering through deployment and operations. Based on Harvard ML Systems course and Designing ML Systems by Chip Huyen.

doanchienthangdev
doanchienthangdev
data-ai
open
machine-learning
1

plan-mode

AEGISモデルのARC-Challenge改善、GSM8K健全性検証、GRPO報酬多目的化のための包括的Planモード。頑健な回答抽出、タイムアウト最適化、データ汚染チェック、複数seed評価、汎化性能向上を実装。

zapabob
zapabob
data-ai
open
machine-learning
1

ml-monitoring

Production-grade ML model monitoring, drift detection, and observability

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

adversarial-machine-learning

Guide for adversarial machine learning: adversarial examples, data poisoning, model backdoors, and evasion attacks.

gmh5225
gmh5225
data-ai
open
machine-learning
1

ml-expert

Expert-level machine learning, deep learning, model training, and MLOps

personamanagmentlayer
personamanagmentlayer
data-ai
open
machine-learning
1

machine-learning

Python machine learning with scikit-learn, PyTorch, and TensorFlow

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

yaml-configuration

YAML for configuration-driven engineering workflows, model setup, and analysis parameters

vamseeachanta
vamseeachanta
data-ai
open
machine-learning
1

deployment-paradigms

ML deployment paradigms including batch vs real-time inference, online vs offline serving, edge deployment, and serverless ML.

doanchienthangdev
doanchienthangdev
data-ai
open
machine-learning
1

mlops

MLflow, model versioning, experiment tracking, model registry, and production ML systems

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

clustering

Discover patterns in unlabeled data using clustering, dimensionality reduction, and anomaly detection

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

training-optimization

Advanced techniques for optimizing LLM fine-tuning. Covers learning rates, LoRA configuration, batch sizes, gradient strategies, hyperparameter tuning, and monitoring. Use when fine-tuning models for best performance.

ScientiaCapital
ScientiaCapital
data-ai
open
machine-learning
1

ml-fundamentals

Master machine learning foundations - algorithms, preprocessing, feature engineering, and evaluation

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

data-ai

Linux data science and AI/ML environment setup - TensorFlow, PyTorch, CUDA, Jupyter

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

data-engineering

Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

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 cascading failure prediction, (2) implementing self-supervised pretraining for power systems, (3) evaluating cascade explanation fidelity against ground-truth masks, or (4) conducting reproducible ML-for-power-systems research. Triggers include "PowerGraph", "power flow GNN", "OPF surrogate", "cascade prediction", "physics-guided GNN", "grid analytics ML", "power system representation learning".

mhdhazmi
mhdhazmi
data-ai
open
machine-learning
1

organism-conversion-loop

Use when building AI-native products where user data can fine-tune performance, when static software fails to improve with usage, or when designing products that learn from interaction

Coowoolf
Coowoolf
data-ai
open
machine-learning
1

training-pipelines

Master training pipelines - orchestration, distributed training, hyperparameter tuning

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

mechinterp-decoder

Analyze SAE decoder weights - output influence, feature importance, and decoder similarity

cesaregarza
cesaregarza
data-ai
open
machine-learning
1

model-inversion

Privacy attacks to extract training data and sensitive information from AI models

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
machine-learning
1

robust-ai

Building robust AI systems including model monitoring, drift detection, reliability engineering, and failure handling for production ML.

doanchienthangdev
doanchienthangdev
data-ai
open
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