training-data
Training data management including labeling strategies, data augmentation, handling imbalanced data, and data splitting best practices.
Browse published AI skills maintained by doanchienthangdev. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
128Repository stars across indexed skills
384Repository forks
128Average repository stars per indexed skill
3Repository stars may repeat across skills from the same repository.
Training data management including labeling strategies, data augmentation, handling imbalanced data, and data splitting best practices.
Agency-grade interface design with systematic aesthetic framework (BEAUTIFUL → RIGHT → SATISFYING → PEAK)
Claude writes comprehensive Python tests using pytest. Use when writing unit tests, creating fixtures, parametrizing tests, mocking dependencies, testing async code, or setting up CI test pipelines.
Deep learning foundations including neural network basics, backpropagation, optimization, regularization, and training best practices.
Claude builds immersive 3D web experiences with Three.js and React Three Fiber. Use when creating WebGL scenes, 3D animations, shaders, or physics simulations.
The agent enforces mandatory test completion before any task or feature can be marked as done, ensuring code quality through strict validation gates and evidence-based completion criteria.
Building robust AI systems including model monitoring, drift detection, reliability engineering, and failure handling for production ML.
Enterprise Ruby on Rails development with Active Record, API mode, testing, and production patterns
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.