MATLAB 2014b - Must Have Tool For Data Scientists
Written by Alex Armstrong   
Tuesday, 28 October 2014

The latest release of MATLAB features a new graphics system for better visualization and new functions for processing big data on your desktop that can scale for use with Hadoop. This makes it even more powerful for working with big data.

Mathworks MATLAB describes itself as:

a high-level language and interactive environment for numerical computation, visualization, and programming.

With data science being the new hot topic MATLAB, and its open source counterpart Octave which admittedly lacks the most recent bells and whistles, is increasingly popular for a high-level language and interactive environment for analyzing data, developing algorithms.

It is also a good language to put on your resume. Speaking at book-promotion for the recently published "How Google Works", Google’s former Product Management Jonathan Rosenberg is quoted as saying:

If you want to work at Google, make sure you can use MATLAB to good effect.

Released this month, MathWorks 2014b, which also includes the model building tool Simulink, is a big update for MATLAB.

The new graphics system which presents data more accurately, making it easier to interpret is introduced in this video:

 

 

As well as new default line colors, fonts, and styles its anti-aliased fonts and lines provide smoother text and graphics. Its graphics objects are easier to use and provide a simple syntax for changing properties. 

For working with big data MATLAB 2014b introduces support for processing data sets too large to fit into memory using MapReduce internally and the Hadoop No-SQL database for external data processing.Other innovations that make large data files easier to process, manage and analyze include operating on 64-bit processors to accommodate more memory and the ability to tap multiple processors using the PARFOR instruction. MATLAB code can also be compiled for NVIDIA GPUs (graphics processing units) and run across GPU arrays. Floating point operations are generally much faster and more efficient using GPUs rather than industry-standard CPUs. 

MATLAB 2014b also has better facilities for collaboration. It introduces Git and Subversion source control integration together with access to projects on GitHub from File Exchange. A new utility enables users to package their custom toolbox as single, installable files for easy sharing and downloading.

Other new features include:

  • Date and time data types with time zone and display options

  • Arduino and Android hardware support for interacting with motors and actuators, and for accessing sensor data

  • Client libraries for use with C/C++ and Python environments in the MATLAB Production Server

  • Multiclass machine-learning framework for binary classifiers such as SVM, and for generalized linear mixed-effects (GLME) models in the Statistics Toolbox

  • Bloomberg B-PIPE and Thomson Reuters Eikon connectivity in the Datafeed Toolbox

  • Image segmentation app, region analysis app, and C code generation for 19 functions with MATLAB Coder in the Image Processing Toolbox

  • Fill-in-the-blanks Word and HTML forms for enhanced custom reports in the MATLAB Report Generator

If you are interested in getting a hands-on introduction to MATLAB, Iversity offers an interdisciplinary MOOC, taught in English by Prof Georg Fries. The original presentation of Modelling and Simulation using MATLAB has concluded but its materials can still be audited online.

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More Information

MATLAB

MathWorks Introduces New Features in MATLAB and Simulink

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Last Updated ( Tuesday, 28 October 2014 )