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Model-Development standards for model development in Ml Ai environments.
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Kubernetes standards for container orchestration, deployments, services, ingress, ConfigMaps, Secrets, and security policies. Covers production-ready configurations, monitoring, and best practices for cloud-native applications.
Master Kotlin coding standards with null safety, coroutines, and idiomatic patterns. Use when developing JVM/Android applications requiring type-safe async programming.
Comprehensive coding standards and best practices for maintainable, consistent software development across multiple languages and paradigms
React frontend standards covering hooks (useState, useEffect, useContext, custom hooks), state management (Context API, Redux, Zustand), performance optimization (memoization, lazy loading, code splitting), testing with React Testing Library, and accessibility (WCAG 2.1, ARIA) for modern SPAs
Security Operations Center (SOC) practices, incident response, SIEM management, and threat hunting following NIST 800-61
| name | model-development |
| description | Model-Development standards for model development in Ml Ai environments. |
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This skill covers essential practices for ml ai.
Key areas include:
Apply these patterns when working with ml ai:
Avoid these common mistakes:
See the templates/ directory for starter configurations.
Consult official documentation and community best practices for ml ai.
