Distributed Machine Learning with Python: Accelerating model training and serving with distributed systems

Build and deploy an efficient data processing pipeline for machine learning model training in an elastic, in-parallel model training or multi-tenant cluster and cloudKey Features: Accelerate model training and interference with order-of-magnitude time reduction Learn state-of-the-art parallel schemes for both model training and serving A detailed study of bottlenecks at distributed model training and serving stages Book Description: Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in t