Tag: ml-quant-dev
Concepts
- Dataloader Throughput and GPU Utilisation
- Distributed Training on Panel Data
- Designing Feature Pipeline DAGs
- Hot-Reloading Models Without Downtime
- Running Hyperparameter Sweeps at Scale
- Immutable Training-Set Snapshots
- Incremental vs Full Feature Recomputation
- Leakage Tests in Continuous Integration
- Packaging and Serialising Model Artefacts
- Model Rollback and Freeze Procedures
- Nondeterminism in GPU Training
- ONNX and Cross-Language Model Export
- Quantisation and Pruning for Latency
- Sweep Result Databases and Model Leaderboards
- Unit Tests for Feature Transforms