The machine-learning renaissance
summary
Argues that a true machine learning renaissance arrives only when abundant data meets a platform to manage it, and names the two technical enablers as Hadoop and Spark. Claims Spark largely supplants MapReduce for new work and lets teams train and deploy scale‑out ML far faster, with libraries like MLlib and TensorFlow integrated and optimized with vendor help including Intel and its 15 billion dollar Mobileye move. Reports more than 400+ customers running Spark in production on ML workloads.
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