nickcdryan
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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”:
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Flexible Python: Product of a List
How many different ways can we multiply the elements of a variable-length list in Python?
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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…
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MLE, MAP, and Naive Bayes
Suppose we are given a dataset of outcomes from some distribution parameterized by . How do we estimate ? 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?
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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…
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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…
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Understanding Facebook Ads: Pros and Cons
I recently did some A/B testing work through the Facebook advertising platform, and gave a quick presentation on the pros and cons of the platform. Here’s a summary. PRO Microtargeting Optimization Inexpensive, low ceilings Demonstrated to work at scale, sophisticated distribution CON Click bots Opaque To clarify my perspective on the platform, some background on the…
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Decorators and Metaprogramming in Python
Decorators Decorators are intuitive and extremely useful. To demonstrate, we’ll look at a simple example. Let’s say we’ve got some function that sums all numbers 0 to n: and we’d like to time the performance of this function. Of course we could just modify the function like so:
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Shallow Parsing for Entity Recognition with NLTK and Machine Learning
Getting Useful Information Out of Unstructured Text Let’s say that you’re interested in performing a basic analysis of the US M&A market over the last five years. You don’t have access to a database of transactions and don’t have access to tombstones (public advertisements announcing the minimal details of a closed deal, e.g. ABC acquires XYZ for…
Nick Ryan 