Ray Data - Scalable ML Data Processing Distributed data processing library for ML and AI workloads. When to use Ray Data Use Ray Data when: - Processing large datasets ( 100GB) for ML training - Need distributed data preprocessing across cluster - Building batch inference pipelines - Loading multi-modal data (images, audio, video) - Scaling data processing from laptop to cluster Key features : - Streaming execution : Process data larger than memory - GPU support : Accelerate transforms with GPUs - Framework integration : PyTorch, TensorFlow, HuggingFace - Multi-modal : Images, Parquet, CSV, J…