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
Pinpointing the most useful machine learning data and figuring out how to combine sources to create accurate, meaningful models is one of the most business-critical areas
We’d all like to imagine that the machines, systems, and algorithms we create are objective and neutral, devoid of prejudice, free from pesky human weaknesses like
There are some insights that can only come from the data you produce or collect in-house. Historical sales figures, for example. Foot traffic through your store.
Data science websites overflow with tips for organizing and handling your data, improving visibility and gaining insight into your company’s performance. The question is, though: how
You don’t know what you don’t know, as the old saying goes. But in the age of Big Data, you simply can’t afford to shrug off
The field of machine learning is currently experiencing a rapid and booming expansion that seems to have no end. It seems like every other day, the