Machine Learning

Not to sound alarmist or anything, but machine learning (ML) initiatives can be risky. It’s true, they sound amazing, and you hear success stories left and right about the transformative power of ML. But, the hype sometimes drowns out the reality. The rush to get ML projects online is understandable, as they have real, tangible […]

Like Italian cooking, data science is all about quality ingredients. It’s not enough to simply have a lot of data; you need to make sure the data you have is good. That it’s relevant for your purposes. That it’s cleaned and prepared right. That you have enough of the data you need and have removed […]

A few years ago, a friend of mine was traveling solo through Kazakhstan when he got chatting to a friendly local who described himself as an emcee. Now, my friend is a huge hip-hop fan, so he was very enthusiastic to find out more about the Almaty rap scene. “You wanna see some of my […]

There’s nothing more frustrating than laboring away at the early stages of your data science project, only to discover that the success of your model is undermined by mistakes or oversights made from the outset. Data preparation takes time and care to get right — and if you do, you’ll be off to an excellent […]

Who could possibly have known, back in those carefree days of early January 2020, that the best-selling items of the coming months — the products to really fly off the shelves around the world — would be face masks, hand sanitizer, and toilet paper? But then, who could have known at the start of 1996 […]

The bad hire has been a problem in recruiting for as long as we’ve been doing it, but it seems that no matter how we try, it’s hard to predict how well someone will pan out once they actually start their job. Even in today’s data-rich world, with the incredibly granular view we have of […]

So, you’ve built a dataset you’re happy with, and your machine learning (ML) model ready to start making predictions left and right. Easy as pie, right? Well, it depends. Once you have a dataset that’s worth using to train your models, you need to build a feature set that will actually get you the predictions […]

When Ford released the Edsel, its brand-new, mid-range model, in 1957, the company was confident it would blow the competition out of the water. After all, Ford had spent ten years and $250 million developing this car. They’d conducted extensive, exhaustive market research. The data they’d painstakingly accumulated suggested the Edsel would easily outperform sales […]

For nine seasons of (now classic) television, The Office’s Dunder Mifflin Paper Company somehow managed to skate by in an industry that has been experiencing a long, slow decline as the world becomes more digital. In Scranton, where the show is based, regional manager Michael Scott somehow manages (despite his best efforts) to build a […]

Your machine learning model is only as good as the data you feed into it. That makes data preparation for machine learning (or cleaning, wrangling, cleansing, pre-processing, or any other term you use for this stage) incredibly important to get right. It will likely take up a considerable chunk of your time and energy. Data […]

In the world of TV’s Parks and Recreation, few people are as concerned about their image and how they market themselves as Tom Haverford. The erstwhile entrepreneur loves to think up business ideas that range from the quirky (a submarine-themed club named “Club-a-Dub-Dub”) to the successful (tween clothes rental store “Rent-a-Swag”), to the plain bizarre […]

It takes Marty Byrde less than three episodes of television to go from white-collar embezzler at a major bank to blue-collar money launderer for the Mexican drug cartels. And boy, does he make it look easy. The money laundering schemes at the heart of Netflix’s hit show OZARK are slick and surprisingly low-tech. While today’s […]

Data science for business is a very different beast than building models in an academic or purely scientific context. You aren’t looking for patterns simply because they’re food for thought, inspire further questions, or demonstrate interesting dynamics and behaviors. You’re looking for patterns because someone in your company wants to know what action they should […]

When you make accurate predictions, you make smarter business decisions. This is the core value data science offers to marketers. It’s easy to get caught up in the buzzwords, but AI marketing automation and machine learning tools will only help you if a) you know exactly what you’re looking for, and b) you can communicate […]

AI has become a buzzword, even as machine learning (ML) and data science push toward automation. We’ve all seen a million articles about how AI will revolutionize this or that, from agriculture to video games. The hype is enough to make anyone skeptical. But in terms of real impact, few areas have really maximized the […]

A good data scientist is a bit like a good journalist: they know how to ask questions so precise and to the point that there can be no vague, misleading answer. Data science is all about asking these sharp, specific questions of your data — and the techniques involved in machine learning guides you to […]

We’re living through unprecedented times. Until this moment, organizations were successfully using data science models, machine learning, and other types of AI across the funnel to gain visibility throughout their business and sharpen their competitive edge. Suddenly, many of these organizations find themselves stumped. Without warning, the data — and in many cases the models […]

Data science and AI have enormous potential to make your organization run more efficiently and profitably. They can be used to optimize processes, identify emerging risk and fraud attempts, spot emerging commercial opportunities, and serve your customers better. You know that. Your team knows that. But does the rest of your organization know? Top data […]