Code Monkey home page Code Monkey logo

multivariate-analysis's Introduction

mva -- Multi Variate Analysis

This repository recoups a number of projects in multivariate analysis. Some of the content can be viewed as a preliminary for Deep Learning applied to the same data set.

Content:

Some of the work presented here is concerned with mere toy examples meant for others to hone their MVA skills. They are mostly those in folders named Lab1, Lab2, etc. Other developments are more personal and involve a greater amount of coding using R and / or python scripting.

Data-sets:

Some of the public domain data set used to perfom analyses were not uploaded on this repo due to the size limitation on individual files imposed by GitHub. In such cases at least a snapshot of the data sets is provided as well as a URL, where it can be downloaded. The downloaded data set may or may not be identical to the one originally used to obtain results presented here. The responsability for that falls squarely on the data maintainer. In practice however, interested people may still benefit from the strategy laid out to deal with the data, irrespectively of whether some of the data as changed. Data set changes over the years (if any) are likely to be all or nothing in any case; i.e. a data set may cease to be available because the website has disappeared or moved.

Licensing terms and copyright:

Feel free to copy any material found here and to further release it to the general public, subject to the terms of the GNU General Public License v3... That license is not a right granted to you to plagiarize the content of the repo. Your editor, your university, your mother and common decency all have rules against that. So use common sense and live happily ever after.

TLDR: Basically the material on this repo is available for free (as in "free beer") as long as you always attach the above mentioned license's terms to it and you always mention its author’s full names. You may not include it in other work, program, product or applications (commercial in nature or not) which do not comply with the GNU General Public License v3 or with something "very very very close".
Of course the above one sentence summary cannot be considered authoritative or binding in terms of licensing. It does not replace the GNU General Public License v3 included in this repo, which recoups the complete licensing terms for your reading pleasure. ;-)

The copyright however stays with me and with any contributors to this repo, according to who contributed what to the contents of the repo.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.