Supervised vs Unsupervised Machine Learning (ML): What’s the Difference?



I’m going a little bit further. We have really two different types of machine learning versus supervised machine learning, and the second is unsupervised. It’s a supervised machine learning. It really requires you to teach your AI system how to interpret that data. Right so examples of that are, you know, you’re creating your own modeling, write your own algorithms, could be asking an AI. How many subscribers are likely to the next? Or how many people, what specific content, asset and specific region? Now, unsupervised, small, you know, that means that the algorithms. They’re learning on their own, right, they’re answering questions and finding patterns that humans didn’t think to ask. So some examples of these might be unsupervised. I finding poor content recommendations or maybe even a more specific example would be a subscriber whose is an annual subscription payment. And then immediately and their subscription center, they choose to not renew. Now, that triggers them being put on an incorrect marketing campaign, trying to win the subscriber back when the reality is they just started their journey. So both supervised and unsupervised, Mel and I are very valuable, and later on, we’ll discuss how and which platform, you can choose and have the greatest impact. And the quality of your machine.