Distributed Data Parallelism (Distributed Parallel Training, often abbreviated as DDp) represents a significant technique for scaling ML model training across several devices, like GPUs or machines. This approach https://ddp782777.veronicablog.com/61908274/distributed-data-guide-to-parallel-processing