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?
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,
With so much data in your own stores, it’s tempting to think you have all you need to start producing great predictive insights. This might be
Your machine learning model is only as good as the data you feed into it. That makes data preparation (or cleaning, wrangling, cleansing, pre-processing, or any
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
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
Congratulations! You’ve embraced machine learning and data science and your organization is well on its way to building a system that helps you deploy predictive analytics
As you know, every second of every day, we’re generating and acquiring new data. As you read this, someone is collecting data on the fact that
In 2007, two roommates struggling to make rent in San Francisco had a bright idea. A major design conference was coming up and hotel prices were
