Jamison Cush: The machines are watching and learning — and they know when you click. Ever wonder why the ads you see online seem specifically tailored to you? Showing an item you just browsed or purchased? That’s machine learning in action. Machine learning is a type of algorithm that allows software applications to predict outcomes without explicit programming. Programs collect data, in this case, your clicks and searches, look for patterns, and adjust program actions accordingly. It’s big in social media. As you scroll social media apps know when you stop to read, share or like something. They learn the people and things you interact with, and show you more of it in hopes of increasing engagement. With online browsing, recommendation engines use machine learning to keep track of your searches, purchases, and clicks to personalize online ads in almost real time. Machine learning can be supervised or unsupervised. Supervised machine learning is task driven, requiring a data science test or analyst to provide both input and desired output and determine which variables the model should analyze. Unsupervised algorithms, on the other hand, are not trained with desired outcomes in mind. They are data driven, and they use deep learning to review data and arrive at conclusions. Machine learning platforms are among enterprise technology’s most competitive realms, with major vendors like Amazon, Google, Microsoft and others competing to sign up customers for machine learning services.