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Recently Apache Ignite 2.0 introduce a beta version of the in-memory machine learning grid, which is a distributed machine learning library built on top of the Apache IMDG. This beta release of ML library can perform local and distributed vector, decompositions and matrix algebra operations. The data structure can be stored in Java heap, off-heap or distributed Ignite caches. At this moment, the Apache Ignite ML grid doesn't support any prediction or recommendation analysis. In this short post, we are going to download the new Apache Ignite 2.0 release, build the example and run them. 1. Download and unpack the Apache Ignite 2.0 distribution. Download the Apache Ignite 2.0 binary release version from the following link . Unpack the distribution somewhere in your workstation (e.g /home/ignite/2.0 ) and set the IGNITE_HOME path to the directory. 2. Start the Apache Ignite remote node Run the following command in the terminal window. ignite.sh examples/config/example-ignite....

One of my friend ask me to develop a course for students in subject "Machine Learning". Course should be very simple to familiar students with machine learning. Main purpose of this course is to explorer the machine learning world to the students and playing over this topics with own their hands. Machine learning is very much matured and a lot of tools and frameworks is available to wet your hands in this topics, however most of the articles or tutorials you could found in the internet will start installing cluster or have to write a bunch of code (even, in site mahout, they are using maven) to start learning. Even more not all students are familiar with hadoop or do not have very powerful notebook to install and run all the components to get test of machine learning. For these reasons i have got the following approach: Standalone Hadoop Standalone Mahout  And a few CSV data files to learn how to works with Predictions Assume you already have java installed in your work s...