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Ross's Blog » Blog Archive » Toolbox for learning machine learning and data science

http://k2company.com/blog/2012/09/06/toolbox-for-learning-machine-learning-and-data-science/ Posted: September 6th, 2012 | Author: admin | Filed under: Uncategorized | 8 Comments » Recently I jumped in and taught myself how to do medium-sized data exploration and machine learning. (Excel-sized < My Data Set < Big Data)
(This post is elementary: it introduces a simple method of visualizing Bayesian calculations. In my defense, we've had other elementary posts before, and they've been found useful; plus, I'd really like this to be online somewhere, and it might as well be here.) I'll admit, those Monty-Hall - type problems invariably trip me up.

Bayes' Theorem Illustrated (My Way)

http://lesswrong.com/lw/2b0/bayes_theorem_illustrated_my_way/
Source code for this article may be found here . Note for nerds: The code shown in this article may be incomplete and may not contain all the security checks you would usually perform in your code as it is given here for demonstration purposes only. Downloadable source code may contain bugs (there is no software without bugs at all). http://syprog.blogspot.com/2012/03/trivial-artificial-neural-network-in.html

Trivial Artificial Neural Network in Assembly Language

http://blogs.adobe.com/digitalmarketing/personalization/conversion-optimization/understand-the-math-behind-it-all-bayesian-statistics/ Most mar­ket­ing peo­ple have only a pass­ing inter­ac­tion with sta­tis­tics, and often times only under­stand it as a mea­sure of how it has impacted their daily life. One of the funny things peo­ple don’t real­ize is that there are two com­pletely dif­fer­ent com­pet­ing schools of thought when it comes to sta­tis­tics. Most peo­ple are famil­iar with fre­quen­tist sta­tis­tics, hav­ing dealt with things like nor­mal dis­tri­b­u­tion, bell curves, and estab­lished prob­a­bil­i­ties.

Understand the Math Behind it All: Bayesian Statistics | Adobe Digital Marketing Blog

http://code.google.com/p/ourmine/wiki/LectureNaiveBayes A Bayes classifier is a simple statistical-based learning scheme. Advantages: Tiny memory footprint Fast training, fast learning Simplicity Often works surprisingly well

LectureNaiveBayes - ourmine - NaiveBayes Classifiers 101 - data mining toolkit

Game | AI/Etc - Tech Topics

http://yudkowsky.net/rational/bayes

Bayes' Theorem

Bayes' Theorem for the curious and bewildered; an excruciatingly gentle introduction. Your friends and colleagues are talking about something called "Bayes' Theorem" or "Bayes' Rule", or something called Bayesian reasoning. They sound really enthusiastic about it, too, so you google and find a webpage about Bayes' Theorem and... It's this equation. That's all. Just one equation.
How To Build a Naive Bayes Classifier

Scaling/Big Data/Distributed/Etc | Technology Topics

Computer Vision/Object Recognition | Technologies