Learn the difference between supervised ML, unsupervised ML, and reinforcement learning. Test your knowledge of machine learning techniques with an interactive infographic.
The quiz below was made to help you test your knowledge of supervised ML, unsupervised ML, and reinforcement learning while understanding which machine learning techniques fall under these categories. Try it or even embed it into your webpage!
Supervised machine learning techniques
In supervised machine learning models, we give the model a dataset with the answers (labels) to learn how to predict the label(s) for other examples where the labels are unknown.
Reinforcement learning, on the other hand, is not trained with the answer. Instead, an agent is either penalized or rewarded for interacting with the environment. It learns from previous attempts and tries to maximize the reward with each attempt.
Unsupervised machine learning techniques
Unsupervised machine learning algorithms find hidden structures between the attributes (features) when the given dataset does not include labels. This is different from supervised learning; in that, we don’t tell the model what it needs to learn.