Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification. Many of the implementations use the Apache Hadoop platform. Mahout also provides Java libraries for common maths operations (focused on linear algebra and statistics) and primitive Java collections. Mahout is a work in progress; the number of implemented algorithms has grown quickly, but various algorithms are still missing.
Miri Infotech is launching a product which will configure and publish Mahout, to produce free implementations of distributed or otherwise scalable machine learning algorithms which is embedded pre-configured tool with Ubuntu and ready-to-launch VM on Azure that contains Mahout, Hadoop, Scala, Sparks.
Apache Spark is a powerful open source processing engine for Hadoop data built around speed, easy to use, and sophisticated analytics. It was originally developed in UC Berkeley’s AMPLab and later-on it moved to Apache. Apache Spark is basically a parallel data processing framework that can work with Apache Hadoop to make it extremely easy to develop fast, Big Data applications combining batch, streaming, and interactive analytics on all your data.
Scala is a modern multi-paradigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala has been created by Martin Odersky and he released the first version in 2003. Scala smoothly integrates the features of object-oriented and functional languages. This tutorial explains the basics of Scala in a simple and reader-friendly way.
Apache Mahout is an open source project that is primarily used for creating scalable machine learning algorithms. It implements popular machine learning techniques such as:
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Recommendation
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Classification
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Clustering
Apache Mahout started as a sub-project of Apache’s Lucene in 2008. In 2010, Mahout became a top level project of Apache.
Scala Features:
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Scala is object-oriented
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Scala is functional
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Scala is statically typed
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Scala runs on the JVM
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Scala can Execute Java Code
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Scala can do Concurrent & Synchronize processing
Spark Features:
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Lighting Fast Processing
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Support for Sophisticated Analytics
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Real Time Stream Processing
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Active and Expanding Community
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Ease of Use as it supports multiple languages
User interaction features include:
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The algorithms of Mahout are written on top of Hadoop, so it works well in distributed environment. Mahout uses the Apache Hadoop library to scale effectively in the cloud.
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Mahout offers the coder a ready-to-use framework for doing data mining tasks on large volumes of data.
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Mahout lets applications to analyze large sets of data effectively and in quick time.
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Includes several MapReduce enabled clustering implementations such as k-means, fuzzy k-means, Canopy, Dirichlet, and Mean-Shift.
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Supports Distributed Naive Bayes and Complementary Naive Bayes classification implementations.
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Comes with distributed fitness function capabilities for evolutionary programming.
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Includes matrix and vector libraries.