A new freeCodeCamp course teaches Distributed Data Parallelism (DDP) for scaling AI model training across multiple GPUs. The 2-hour course covers the theory behind distributed training, differences between data parallelism and model parallelism, manual batch averaging, the All Reduce operation, and DDP hooks for optimizing training workflows. It targets developers looking to overcome memory limitations when training large models.
958 Impressions