ML Training Pipeline

Coming soon.

This page will show a machine learning training pipeline in OxyMake, covering:

• Data preparation: feature extraction, train/test splitting, and normalization
• Hyperparameter sweeps: wildcard-driven grid search across learning rates, architectures, and regularization parameters
• GPU resource management: declaring GPU requirements per rule for SLURM/Kubernetes scheduling
• Model evaluation: automated metric collection and comparison
• In-memory passing: using call mode with Arrow IPC to pass DataFrames between feature computation and training without disk I/O