Free Linear Regression Software Download

Software

Software Password

Click Here to Join Our Community to Obtain the Current Password!

Some episodes of Learning Machines 101 introduce software which can be downloaded. In order to download the software you must first obtain the current password which is available for free when you join the Learning Machines 101 community. The software password will be changed from time to time. As a member of the Learning Machines 101 Community, you will be informed of the current software password as well as announcements regarding recent podcasts, software updates, and special events such as webinars. Membership is free and you can cancel your membership at any time. Typically, you should receive about 2 emails per month from Learning Machines 101.

MATLAB Software (Source Code)

MATLAB Source Code for both Windows Executable and MAC OS-X Executable Versions will typically be provided. The MATLAB Source Code requires that you have already installed the MATLAB Software Development Environment (see: www.mathworks.com)  on your computer in order for you to execute the MATLAB Source Code. However, even if you are unable to execute the MATLAB Source Code you may find it helpful to download the MATLAB Source Code if you are interested in the specific algorithms used in the software. The MATLAB Source Code is written in such a way that it is easy to read and it clearly documents the relevant algorithms.

Download Linear Machine Software

How to Run Executable Software on Windows or MAC OS-X

In order to run executable software provided on this website, you must download and install either the Windows MCR Library Installer Version 2011b 32-bits  or  the  MAC OS-X MCR Library Installer Version 2012a 64-bits. This is a one-time installation. This file is approximately 300 megabytes (1/3 of a gigabyte) so it is very large. Do not delete this “installer file” after you download it because if you decide to remove the MCR Library from your computer in the future, you will need this  files to do a “clean” uninstall of the MCR Library software. Once the MCR Library software is uninstalled, you can then delete the installer file.   Finally, it is legal for you to download and install the MCR Library Installer on your computer only for the purpose of running the executable software provided by Learning Machines 101 on this website.

Also please note that if you are using a very recent version of MAC OS-X you may have to download Xquartz from  http://xquartz.macosforge.org/landing/

Click here to download the installer for your operating system.

 

APACHE 2.0 Software License

All MATLAB source code is provided under the APACHE 2.0 license. Check out: Bob Butterfield’s informal explanation of the official APACHE 2.0 license which is located at: http://www.apache.org/licenses/LICENSE-2.0.html The bottom line is simply the Apache 2.0 license allows you to use, modify, and distribute the software as long as you keep the relevant LICENSE.txt notices associated with the software intact. You can incorporate this free software into your commercial projects royalty free without requiring additional permission from RMG Consulting Inc. Also if you are working under the GNU license which is an open-source license, you can incorporate this code into GNU open-source projects as well. The APACHE 2.0 license also says that if there is a software bug in the code or an algorithm design problem with this software and you use it in your project and consequently your project or some outcome of that project suffers because of that software bug or design problem, you can’t attribute the blame to the owner of the software which is RMG Consulting Inc. Please note further the current software is under active development and refinement and despite my best efforts may have software bugs or algorithm design flaws. This software has not been extensively tested and is therefore likely to have bugs and algorithm design flaws.

Reporting Software Bugs

Please post bugs and algorithm design flaws on this comments page to inform all users of the Learning Machines 101 Community as well as providing direct feedback using the link: www.learningmachines101.com/contact.

 

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