Vqc trainer
Skill a5c-ai/babysitter/library/specializations/domains/science/quantum-computing/skills/vqc-trainer
Variational quantum classifier training skill with gradient optimizationFrom its SKILL.md
npx -y skills add a5c-ai/babysitter --skill vqc-trainerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
1.5 KB, 190 tokens by cl100k_base, as published. Nobody here has run it
VQC Trainer
Purpose
Provides expert guidance on training variational quantum classifiers, including data encoding, circuit design, and gradient-based optimization.
Capabilities
- Data encoding circuit design
- Variational layer construction
- Gradient-based optimization (SPSA, Adam)
- Cross-validation for QML
- Hyperparameter tuning
- Overfitting detection
- Learning curve analysis
- Ensemble methods
Usage Guidelines
- Data Preparation: Preprocess classical data for quantum encoding
- Encoding Design: Select appropriate data encoding strategy
- Ansatz Design: Build variational circuit with trainable parameters
- Training Setup: Configure optimizer, learning rate, and batch size
- Evaluation: Assess model on test set with proper metrics
Tools/Libraries
- Qiskit Machine Learning
- PennyLane
- TensorFlow Quantum
- PyTorch
- scikit-learn
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.