Module 5: Training Infrastructure
๐ฏ Learning Objectivesโ
- Manage GPU/TPU resources effectively for ML training
- Implement distributed training strategies (data parallelism, model parallelism)
- Use cloud training platforms (AWS SageMaker, GCP Vertex AI, Azure ML)
๐ Module Contentโ
Chapter 1: GPU/TPU Managementโ
Hardware selection, GPU memory optimization, multi-GPU training, cost management.
Chapter 2: Distributed Trainingโ
Data parallelism, model parallelism, Horovod, PyTorch DDP, DeepSpeed.
Chapter 3: Cloud Training (AWS, GCP, Azure)โ
SageMaker, Vertex AI, Azure ML, spot instances, cost optimization strategies.
๐ Let's Begin!โ
Start with Chapter 1: GPU/TPU Management.