Style Transfer with Tensorflow

A Neural Algorithm of Artistic Style” is an accessible and intriguing paper about the distinction and separability of image content and image style using convolutional neural networks (CNNs). In this post we’ll explain the paper and then run a few of our own experiments.

To begin, consider van Gogh’s “The Starry Night”: Continue reading “Style Transfer with Tensorflow”

The Box-Cox Transformation

The Box-Cox transformation is a family of power transform functions that are used to stabilize variance and make a dataset look more like a normal distribution. Lots of useful tools require normal-like data in order to be effective, so by using the Box-Cox transformation on your wonky-looking dataset you can then utilize some of these tools.

Here’s the transformation in its basic form. For value $x$ and parameter $\lambda$:

$\displaystyle \frac{x^{\lambda}-1}{\lambda} \quad \text{if} \quad x\neq 0$

$\displaystyle log(x) \quad \text{if} \quad x=0$

MLE, MAP, and Naive Bayes

Suppose we are given a dataset $X$ of outcomes from some distribution parameterized by $\Theta$. How do we estimate $\Theta$?

For example, given a bent coin and a series of heads and tails outcomes from that coin, how can we estimate the probability of the coin landing heads? Continue reading “MLE, MAP, and Naive Bayes”

Text Classification at Data Science Hackathon with DataKind

Last weekend I attended a DataKind data science hackathon. It was a lot of fun and a great way to meet people in the space and share some ideas. If it sounds the least bit interesting, I encourage you to join a DataKind event. Here’s what my team worked on, which should serve as a good indication what you might do over the course of the weekend. My code here: project folder, supervised classification – most interesting, and topic modeling. Continue reading “Text Classification at Data Science Hackathon with DataKind”

A Few Nice Coding Challenges

A recent interview process required passing some coding challenges.

When I first started programming I spent a decent amount of time on Project Euler, but since then I rarely do these crack-the-interview coding challenges. I find project-based work more interesting, I work mostly with data, and – based on what I understand from experienced interviewers – facility with brain teasers and coding challenges correlates less with good programming than time spent programming correlates with good programming. Anyway, I spent a few afternoons working through coding challenges on Codility to get a feel for the types of questions that get asked of software engineering candidates. Continue reading “A Few Nice Coding Challenges”