About

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:

Recommendation
Classification
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:

Scala is object-oriented
Scala is functional
Scala is statically typed
Scala runs on the JVM
Scala can Execute Java Code
Scala can do Concurrent & Synchronize processing

Spark Features:

Lighting Fast Processing
Support for Sophisticated Analytics
Real Time Stream Processing
Active and Expanding Community
Ease of Use as it supports multiple languages

User interaction features include:

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.
Mahout offers the coder a ready-to-use framework for doing data mining tasks on large volumes of data.
Mahout lets applications to analyze large sets of data effectively and in quick time.
Includes several MapReduce enabled clustering implementations such as k-means, fuzzy k-means, Canopy, Dirichlet, and Mean-Shift.
Supports Distributed Naive Bayes and Complementary Naive Bayes classification implementations.
Comes with distributed fitness function capabilities for evolutionary programming.
Includes matrix and vector libraries.

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You can subscribe to Mahout, an AWS Marketplace product and launch an instance from the Mahout product's AMI using the Amazon EC2 launch wizard.

Type virtual machines in the search.
Under Services, select Virtual machines.
In the Virtual machines page, select Add. The Create a virtual machine page opens.
In the Basics tab, under Project details, make sure the correct subscription is selected and then choose to Create new resource group. Type myResourceGroup for the name.*.
Under Instance details, type myVM for the Virtual machine name, choose East US for your Region, and choose Ubuntu 18.04 LTS for your Image. Leave the other defaults.
Under Administrator account, select SSH public key, type your user name, then paste in your public key. Remove any leading or trailing white space in your public key.
Under Inbound port rules > Public inbound ports, choose Allow selected ports and then select SSH (22) and HTTP (80) from the drop-down.
Leave the remaining defaults and then select the Review + create button at the bottom of the page.
On the Create a virtual machine page, you can see the details about the VM you are about to create. When you are ready, select Create.

It will take a few minutes for your VM to be deployed. When the deployment is finished, move on to the next section.

Connect to virtual machine

Create an SSH connection with the VM.

Select the Connect button on the overview page for your VM.
In the Connect to virtual machine page, keep the default options to connect by IP address over port 22. In Login using VM local account a connection command is shown. Select the button to copy the command. The following example shows what the SSH connection command looks like:

bashCopy

ssh azureuser@10.111.12.123

Using the same bash shell you used to create your SSH key pair (you can reopen the Cloud Shell by selecting >_ again or going to https://shell.azure.com/bash), paste the SSH connection command into the shell to create an SSH session.

1What is Hadoop?

The Apache Hadoop software library allows for the distributed processing of large data sets across clusters of computers using a simple programming model. The software library is designed to scale from single servers to thousands of machines; each server using local computation and storage. Instead of relying on hardware to deliver high-availability, the library itself handles failures at the application layer. As a result, the impact of failures is minimized by delivering a highly-available service on top of a cluster of computers.
2Where does Hadoop find applicability in business?

Hadoop, as a scalable system for parallel data processing, is useful for analyzing large data sets. Examples are search algorithms, market risk analysis, data mining on online retail data, and analytics on user behavior data.
3What is big data security analytics?

Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”
4Is there an easy way to migrate data from Hadoop into a relational database?

The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.
5Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

Front-end use of AI technologies to enable Intelligent Assistants for customer care is certainly key, but there are many other applications. One that I think is particularly interesting is the application of AI to directly support — rather than replace — contact center agents. Technologies such as natural language understanding and speech recognition can be used live during a customer service interaction with a human agent to look up relevant information and make suggestions about how to respond. AI technologies also have an important role in analytics. They can be used to provide an overview of activities within a call center, in addition to providing valuable business insights from customer activity.
6What are the popular machine learning algorithms in use today?
There are many machine learning algorithms in use today, but the most popular ones are:
- Decision Trees
- Naive Bayes Classification
- Ordinary Least Squares Regression
- Logistic Regression
- Support vector machines
- Ensemble Methods
- Clustering Algorithms
- Principal Component Analysis
- Singular Value Decomposition
- Independent Component Analysis

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1What is Hadoop?

2Where does Hadoop find applicability in business?

3What is big data security analytics?

4Is there an easy way to migrate data from Hadoop into a relational database?

5Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

6What are the popular machine learning algorithms in use today?

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