Data ml recommended
ML Training Patterns
Machine learning training patterns covering checkpointing, early stopping, learning rate scheduling, gradient accumulation, mixed precision, and reproducible training loops.
- Difficulty
- advanced
- Read time
- 1 min read
- Version
- v1.0.0
- Confidence
- established
- Last updated
Quick Reference
ML Training: Save checkpoints every N epochs. Early stopping with patience. ReduceLROnPlateau or CosineAnnealing scheduler. Gradient accumulation for large batches. Mixed precision (torch.amp). Set seeds for reproducibility. Log metrics to MLflow/W&B. Validate after each epoch. Keep best model only.
Use When
- Deep learning model training
- Neural network optimization
- Long training runs
- GPU training
Skip When
- Traditional ML (sklearn)
- Inference only
- Quick experiments
ML Training Patterns
Machine learning training patterns covering checkpointing, early stopping, learning rate scheduling, gradient accumulation, mixed precision, and reproducible training loops.