when-developing-ml-models-use-ml-expert
Specialized ML model development, training, and deployment workflow
npx skills add majiayu000/claude-skill-registry --skill when-developing-ml-models-use-ml-expert --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ML Expert - Machine Learning Model Development ## Overview Specialized workflow for ML model development, training, and deployment. Supports various architectures (CNNs, RNNs, Transformers) with distributed training capabilities. ## When to Use - Developing new ML models - Training neural networks - Model optimization - Production deployment - Transfer learning - Fine-tuning existing models ## Phase 1: Data Preparation (10 min) ### Objective Clean, preprocess, and prepare training data ### Agent: ML-Developer **Step 1.1: Load and Analyze Data** ```python import pandas as pd import numpy as np from sklearn.model_selection import train_test_split # Load data data = pd.read_csv('dataset.csv') # Analyze analysis = { 'shape': data.shape, 'columns': data.columns.tolist(), 'dtypes': data.dtypes.to_dict(), 'missing': data.isnull().sum().to_dict(), 'stats': data.describe().to_dict() } # Store analysis await memory.store('ml-expert/data-analysis', analysis) ``` **Step 1.2: Data Cleaning** ```python # Handle missing values data = data.fillna(data.mean()) # Remove duplicates data = data.drop_duplicates() # Handle outliers from scipy import stats z_scores = np.abs(stats.zscore(data.select_dty
- Overview
- When to Use
- Phase 1: Data Preparation (10 min)
- Objective
- Agent: ML-Developer
- Validation Criteria
- Phase 2: Model Selection (10 min)
- Agent: Researcher
- Phase 3: Train Model (20 min)
- Phase 4: Validate Performance (10 min)
- Agent: Tester
- Phase 5: Deploy to Production (15 min)
- Success Metrics
- Skill Completion
What does the when-developing-ml-models-use-ml-expert skill do?
Specialized ML model development, training, and deployment workflow
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill when-developing-ml-models-use-ml-expert --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.