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**The Chevalier and Coursera**

I just began the new Coursera MOOC on probability , given by UPenn Dr. Santosh S. Venkatesh, and at the very first lecture, my interest was piqued with this very interesting idea, called the Chevalier de Méré's Paradox.. If I ask you which is more likely: G...

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Italian Zuckerman harpsichord December 2014

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2014-12-08

5 Photos - View album

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**Un Unpredictable Bug**

There's something deeply fascinating in the fact that complexity can sometimes emerge from simple rules.. Here's a Langton's ant , which is always headed in one of four directions (up, down, left, right), which it changes before going a new step: By turning...

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**DBSCAN Blues**

Suppose I give you this dataset of 2D points (with the added twist that the generating code has been obfuscated, to avoid making the answer too obvious), and ask you to group them into \(k\) meaningful clusters. Is there a way to do it without knowing (or g...

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**K-means vs Louvain**

I'm currently reading Data Smart , a particularly good and entertaining book about machine learning and data science. The somewhat surprising twist in its approach is that it does almost entirely without code, and instead implements and illustrates everythi...

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Google acqui-hires AI startup for.. a lot of money!

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**Robustified Linear Regression**

This post is part of a series, see also: Linear Regression 101 Logistic Regression 101 Softmax Regression 101 Neural Network 101 Let's revisit our toy linear regression problem , and in particular, look at what happens when the data contains a lot of outlie...

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**Neural Network 101**

As this seems to be becoming a series of related posts, see also: Linear Regression 101 Logistic Regression 101 Softmax Regression 101 Neural Network 101 A Cloud of Points ¶ As powerful as it is, a logistic regression model will only ever be able to solve l...

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**Softmax Regression 101**

A Cloud of Points ¶ If logistic regression allows to solve binary classification problems, softmax regression, our third example of a generalized linear model, allows to solve multiclass ones. As before, we build an artificial dataset, this time by first pi...

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**Logistic Regression 101**

A Cloud of Points ¶ We will next tackle the problem of binary supervised classification, using the logistic regression method. The artificial dataset we will use this time is built by sampling random 2D points in the plane, and assigning them a class (0 or ...

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