Natural language processing is a huge sub-field of artificial intelligence that deals with models and representations for natural language. A very common way to represent words, phrases, and documents in modern NLP involves the use of sparse vectors. Here we'll explore a variety of Python libraries ...

Probablistic programming is an expressive and flexible way to build Bayesian statistical models in code. It's an entirely different mode of programming that involves using stochastic variables defined using probability distributions instead of concrete, deterministic values. Stochastic variables can...

Spark is currently one of the hottest open source projects in the big data space, even eclipsing Hadoop in terms of excitement. Originally a Berkley AMPlab project, Spark became a top-level Apache project early last year and has been on a tear ever since. The company now backing Spark – Databricks

This post is part of a series covering the exercises from Andrew Ng's machine learning class on Coursera. The original code for this post is available here. The exercise text is available here. Part 1 - Simple Linear Regression Part 2 - Multivariate Linear Regression In part 2 of the

In this blog post we'll examine some common techniques used in time series analysis by applying them to a data set containing daily closing values for the S&P 500 stock market index from 1950 up to present day. The objective is to explore some of the basic ideas

The topic of this post is perhaps a bit mundane, but after spending a considerable amount of time getting this right, I decided to put together a step-by-step guide so I would remember how to do it next time. And since I already went to the trouble, I might as

One of the deep, dark secrets of machine learning is that beneath all of the math, statistics, and algorithms, there's sort of a "black art" to actually building useful models. I think the reason for this stems primarily from the counter-intuitiveness of working in high-dimensional spaces coupled wi...

Anyone that’s paying attention to the “big data” buzz these days is probably aware of just how hot Hadoop is right now. In fact the hype is so great, and the market so untapped, that adoption is expected to increase 25-fold over the next 5 years. Given that, it’

I think it's a fairly well-accepted observation that we're in the middle of a cloud computing revolution. The cloud is making businesses more agile, lowering the barrier to entry for start-ups, driving seamless user experiences across devices, and empowering individuals with near-limitless computing...

If you've spent any amount of time studying machine learning, especially going out on your own and trying to learn independently with no formal training or guidance, there have probably been times where you've come away feeling daunted by the task in front of you. Where to start? What areas

In part 1 of my series on machine learning in Python, we covered the first part of exercise 1 in Andrew Ng's Machine Learning class. In this post we'll wrap up exercise 1 by completing part 2 of the exercise. If you recall, in part 1 we implemented linear regression

If you've never come across the term "reactive programming" before, or have never heard the word "reactive" mentioned in a software development context, you may be forgiven for being in the dark on the subject. I first learned of the reactive paradigm after coming across something called the Reactiv...

Back in early September, I came across an article on hacker news introducing a brand new class at Stanford called "How to Start a Startup". The class, which was hosted by Y Combinator founder Sam Altman, eschewed the traditional lecture model and instead lined up a series of A-list founders

One of the pivotal moments in my professional development this year came when I discovered Coursera. I'd heard of the "MOOC" phenomenon but had not had the time to dive in and take a class. Earlier this year I finally pulled the trigger and signed up for Andrew Ng's Machine

I've spent a lot of time this year learning about the Python ecosystem. It's not something that I've ever used formally on the job, so I had to sort of go out of my way to get exposed to Python. The reason I was motivated to learn Python stems from