Machine learning is quickly becoming a critical skill for developers to enhance their applications and their careers, better understand data, and to help users be more effective.
In this week's edition of our open source news roundup, we take a look at LinkedIn and Facebook make tools open source, IBM gives Apache Spark a boost, and more! Open source news: June 13 - 19, 2015
One thing is certain: Running an open source company has unique challenges and opportunities. Here are 3 critical lessons I've learned from running Lucidworks.
In this week's edition of our open source news roundup, we take a look at helping earthquake victims in Nepal, OpenMRS and the fight against Ebola, Apple's Siri to leverage Apache Mesos, and more. Open source news roundup: April 25 - May 1, 2015
Apache Spark is an open source cluster computing framework. In contrast to Hadoop’s two-stage disk-based MapReduce paradigm, Spark’s in-memory primitives provide performance up to 100 times faster for certain applications.
Chris Mattmann is a frequent speaker at ApacheCon North America and has a wealth of experience in software design and the construction of large-scale data-intensive systems. His work has infected a broad set of communities, ranging from helping NASA unlock data from its next generation of earth... Read more
ApacheCon is coming up, and within that massive conference there will be a glimmering gem: a forum dedicated to Spark. The Spark Forum will have speakers from the Hive project, the Pig project, and the Sqoop project. Plus, two talks about Spark Streaming—one will be introductory, and the other... Read more
University of Southern California postdoctoral fellow and NASA/JPL researcher Annie Bryant Burgess explains how her PhD is related to her involvement in open source, and tells us what Apache Tika has to do with studying polar data.
Spark's new DataFrame API is inspired by data frames in R and Python (Pandas), but designed from the ground up to support modern big data and data science applications.
How does OpenStack differ from other large, popular open source projects and how do these differences affect the way the project is growing and maturing?