In Episode 24 of '100 Days of Data,' hosts Jonas and Amy dive deep into supervised learning, a foundational concept in machine learning where models are trained using labeled examples. They explore how labels act as the 'answer key' that helps algorithms make predictions — from classifying emails as spam to predicting house prices. The episode breaks down the two main types of supervised learning tasks: classification and regression, and highlights real-world applications in industries like healthcare, automotive, and manufacturing. Jonas emphasizes the importance of data quality, while Amy shares insights into the practical challenges businesses face when labeling data. The discussion also touches on model evaluation metrics and common misunderstandings, such as equating machine learning with full automation. Whether you're in AI or just curious, this episode offers a clear, approachable guide to a key component of intelligent systems.