Spark Summit2017上MLLIB的最新进展

ADMM-BASED SCALABLE MACHINE LEARNING ON APACHE SPARK

MATRIX FACTORIZATIONS AT SCALE: A COMPARISON OF SCIENTIFIC DATA ANALYTICS ON SPARK AND MPI USING THREE CASE STUDIES

Extending Spark Machine Learning: Adding Your Own Algorithms and Tools

Applying Machine Learning to Construction

Building a Large Scale Recommendation Engine with Spark and Redis-ML

Accelerating SparkML Workloads on the Intel Xeon+FPGA Platform

The Key to Machine Learning is Prepping the Right Data

Smart Scalable Feature Reduction With Random Forests

Big Data at Audi: Root Cause Analysis in an Automotive Paint Shop Using MLlib

Machine Learning as a Service: Apache Spark MLlib Enrichment and Web-Based Codeless Modeling

Operationalizing Machine Learning at Scale

Real-Time Machine Learning with Redis, Apache Spark, Tensor Flow, and more