Distributed Deep Learning on HDInsight with Caffe on Spark

Deep learning is impacting everything from healthcare to transportation to manufacturing, and more. Companies are turning to deep learning to solve hard problems, like image classification, speech recognition, object recognition, and machine translation. There are many popular frameworks, including Microsoft Cognitive Toolkit, Tensorflow, MXNet, Theano, etc. Caffe is one of the most famous non-symbolic (imperative) neural network frameworks, and widely used in many areas including computer vision. Furthermore, CaffeOnSpark combines Caffe with Apache Spark, in which case deep learning can be easily used on an existing Hadoop cluster together with Spark ETL pipelines, reducing system complexity and latency for end-to-end learning. HDInsight is the only fully-managed cloud Hadoop offering that provides optimized open source analytic clusters for Spark, Hive, MapReduce, HBase, Storm, Kafka, and R Server backed by a 99.9% SLA.…

Link to Full Article: Distributed Deep Learning on HDInsight with Caffe on Spark

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