{"id":3166,"date":"2017-01-31T00:23:36","date_gmt":"2017-01-31T00:23:36","guid":{"rendered":"https:\/\/www.rsoftsolution.com\/blog\/mxnet-accepted-to-the-apache-incubator.html"},"modified":"2017-01-31T00:23:36","modified_gmt":"2017-01-31T00:23:36","slug":"mxnet-accepted-to-the-apache-incubator","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/mxnet-accepted-to-the-apache-incubator.html","title":{"rendered":"MXNet accepted to the Apache Incubator"},"content":{"rendered":"


\n<\/p>\n

MXNet, Amazon Web Services\u2019 preferred deep learning framework, was accepted to the\u00a0Apache Incubator today.<\/a> Admission to the incubator is the first step necessary for the open-source initiative\u00a0to officially become part of the\u00a0Apache Software Foundation.<\/p>\n

The\u00a0Apache Software Foundation supports the efforts of thousands of developers maintaining open-source projects around the world. The ASF will help MXNet to adopt its tried and true open-source processes. MXNet will also benefit from access to the Apache community.<\/p>\n

MXNet is one of many frameworks to help developers build deep learning models without having to reinvent the wheel for every use case. Above other machine learning methodologies, deep learning has become particularly attractive for mining patterns from large data sets.<\/p>\n

One differentiating capability of MXNet is its relative language agnosticism. Developers can use mainstays like\u00a0C++ and Python in addition to languages like R, Scala, MATLAB and JavaScript.<\/p>\n

Another thing MXNet has going for it is its ability to scale. Late last year when Amazon endorsed the framework<\/a>, it noted that MXNet\u2019s\u00a0throughput was faster than other libraries when increasing the number of GPUs supporting an image analysis algorithm. Amazon also noted that MXNet\u2019s throughput increased with 85 percent efficiency when these\u00a0GPUs were added.<\/p>\n

But in the broader machine learning community, MXNet\u2019s usage lags behind peers like TensorFlow. Amazon\u2019s intent with making MXNet its framework of choice was, in part, to generate interest from developers. AWS is contributing code and documentation to make MXNet more attractive to the ecosystem. A closer relationship with the\u00a0Apache Software Foundation can only help to advance these goals.<\/p>\n

\"Blue<\/p>\n

Blue: TensorFlow, Yellow: Theano, Red: MXNet, Green: DL4J<\/p>\n

<\/p>\n

Featured Image: KTSDESIGN\/SCIENCE PHOTO LIBRARY\/Getty Images<\/small><\/p>\n

Article source: http:\/\/feedproxy.google.com\/~r\/techcrunchIt\/~3\/tjXkR3b7DfM\/<\/p>","protected":false},"excerpt":{"rendered":"

MXNet, Amazon Web Services\u2019 preferred deep learning framework, was accepted to the\u00a0Apache Incubator today. Admission to the incubator is the first step necessary for the open-source initiative\u00a0to officially become part <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[19],"tags":[25],"class_list":["post-3166","post","type-post","status-publish","format-standard","hentry","category-enterprise-software","tag-enterprise"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t