expertise needed
software engineering
Requires general programming and system design skills
7 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Federated Learning | Algorithmic | Architecture/linear Models Architecture/neural Networks +4 | Any | Federated learning enables collaborative model training across multiple distributed parties (devices, organisations, or... | ||
| Runtime Monitoring and Circuit Breakers | Algorithmic | Architecture/model Agnostic Requirements/black Box | Any | Runtime monitoring and circuit breakers establish continuous surveillance of AI/ML systems in production, tracking... | ||
| MLflow Experiment Tracking | Process | Architecture/model Agnostic Requirements/black Box | Any | MLflow is an open-source platform that tracks machine learning experiments by automatically logging parameters, metrics,... | ||
| Data Version Control | Process | Architecture/model Agnostic Requirements/black Box | Any | Data Version Control (DVC) is a Git-like version control system specifically designed for machine learning data, models,... | ||
| Model Development Audit Trails | Procedural | Architecture/model Agnostic Requirements/black Box | Any | Model development audit trails create comprehensive, immutable records of all decisions, experiments, and changes... | ||
| Model Extraction Defence Testing | Testing | Architecture/model Agnostic Requirements/black Box | Any | Model extraction defence testing evaluates protections against attackers who attempt to steal model functionality by... | ||
| Multi-Agent System Testing | Testing | Architecture/model Agnostic Requirements/black Box | Any | Multi-agent system testing evaluates safety and reliability of systems where multiple AI agents interact, coordinate, or... |
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