Apache Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Create dataset loader creator operations. Auto-activating skill for ML Training. Triggers on: dataset loader creator, dataset loader creator Part of the ML Training skill category. Use when working with dataset loader creator functionality. Trigger with phrases like "dataset loader creator", "dat...
--- name: dataset-loader-creator-4dd7e74628b8 description: | Create dataset loader creator operations. Auto-activating skill for ML Training. Triggers on: dataset loader creator, dataset loader creator Part of the ML Training skill category. Use when working with dataset loader creator functionality. Trigger with phrases like "dataset loader creator", "dataset creator", "dataset". allowed-tools: "Read, Write, Edit, Bash(python:*), Bash(pip:*)" version: 1.0.0 license: MIT author: "Jeremy Longshore <jeremy@intentsolutions.io>" --- # Dataset Loader Creator ## Overview This skill provides automated assistance for dataset loader creator tasks within the ML Training domain. ## When to Use This skill activates automatically when you: - Mention "dataset loader creator" in your request - Ask about dataset loader creator patterns or best practices - Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking. ## Instructions 1. Provides step-by-step guidance for dataset loader creator 2. Follows industry best practices and patterns 3. Generates production-ready code and configurations 4. Validates outputs against common standards ## Examples **Example: Basic Usage** Request: "Help me with dataset loader creator" Result: Provides step-by-step guidance and generates appropriate configurations ## Prerequisites - Relevant development environment configured - Access to necessary tools and services - Basic understanding of ml training concepts ## Output - Generated configurations and code - Best practice recommendations - Validation results ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Configuration invalid | Missing required fields | Check documentation for required parameters | | Tool not found | Dependency not installed | Install required tools per prerequisites | | Permission denied | Insufficient access | Verify credentials and permissions | ## Resources - Official documentation for related tools - Best practices guides - Community examples and tutorials ## Related Skills Part of the **ML Training** skill category. Tags: ml, training, pytorch, tensorflow, sklearn--- name: dataset-loader-creator-4dd7e74628b8 description: | Create dataset loader creator operations. Auto-activating skill for ML Training. Triggers on: dataset loader creator, dataset loader creator Part of the ML Training skill category. Use when working with dataset loader creator functionality. Trigger with phrases like "dataset loader creator", "dataset creator", "dataset". allowed-tools: "Read, Write, Edit, Bash(python:*), Bash(pip:*)" version: 1.0.0 license: MIT author: "Jeremy Longshore <jeremy@intentsolutions.io>" --- # Dataset Loader Creator ## Overview This skill provides automated assistance for dataset loader creator tasks within the ML Training domain. ## When to Use This skill activates automatically when you: - Mention "dataset loader creator" in your request - Ask about dataset loader creator patterns or best practices - Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking. ## Instructions 1. Provides step-by-step guidance for dataset loader creator 2. Follows industry best practices and patterns 3. Generates production-ready code and configurations 4. Validates outputs against common standards ## Examples **Example: Basic Usage** Request: "Help me with dataset loader creator" Result: Provides step-by-step guidance and generates appropriate configurations ## Prerequisites - Relevant development environment configured - Access to necessary tools and services - Basic understanding of ml training concepts ## Output - Generated configurations and code - Best practice recommendations - Validation results ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Configuration invalid | Missing required fields | Check documentation for required parameters | | Tool not found | Dependency not installed | Install required tools per prerequisites | | Permission denied | Insufficient access | Verify credentials and permissions | ## Resources - Official documentation for related tools - Best practices guides - Community examples and tutorials ## Related Skills Part of the **ML Training** skill category. Tags: ml, training, pytorch, tensorflow, sklearn
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