To supervise, or not to supervise… that is the question!
Did you know there are two types of machine learning? One of them consists of you hand-holding your algorithm into learning stuff.
DOES YOUR BUSINESS NEEDS AI OR JUST AUTOMATION ?
If you want it to learn what an apple looks like… You just point at an apple with your finger, and the program will learn to recognize it in the future. But the second type is more like throwing it into a fruit crate and saying: “classify my fruits, algorithm”.
We are talking about
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Supervised Learning
The vast majority of machine learning tasks fall into the category of supervised learning. Supervised learning tasks are tasks where individual data points/instances are assigned a label or class. This means we know the data instance’s type in advance. As a result, the machine learning model can learn to recognize which features are correlated with a given class or label. In a supervised learning task, we can check the performance of a machine learning model by comparing the predicted labels to the actual labels.
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Unsupervised Learning
In unsupervised learning tasks, the data points are unlabeled, so it isn’t known what type/class each data point is. An unsupervised learning model must be able to analyze input features, determine what the most important features are, and group data points based on attributes the model finds important. An unsupervised learning algorithm basically creates its own labels/classes for the data points in the dataset.
