From the recent Spark Summit 2016 in San Francisco, the video presentation below by Joseph K. Bradley of Databricks give focus to “Apache Spark MLlib 2.0 Preview: Data Science and Production.” This ...
Xiangrui Meng of Databricks, a committer on Apache Spark, talks about how to make machine learning easy and scalable with Spark MLlib. Xiangrui has been actively involved in the development of Spark ...
As organizations create more diverse and more user-focused data products and services, there is a growing need for machine learning, which can be used to develop personalizations, recommendations, and ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. If you’re starting a new machine learning or deep learning ...
Today to kick off Spark Summit, Databricks announced a Serverless Platform for Apache Spark — welcome news for developers looking to reduce time spent on cluster management. The move to simplify ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...
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