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Scaling Machine Learning for Efficiency
This chapter explores the challenges of scaling machine learning systems in production, focusing on data collection methodologies and model training frameworks. It also addresses communication bottlenecks in distributed training and highlights advancements in techniques and tools that enhance efficiency in training large models, especially transformers.