Machine Learning: Random Forest with Python from Scratch - Labels and Features

The video tutorial introduces the concepts of labels and features in datasets, particularly in the context of supervised machine learning. It explains that labels, also known as targets or classes, are the outputs of data, while features are the measurable properties or characteristics observed. The tutorial discusses the importance of converting non-numeric labels into numeric form for machine learning models. It also highlights the significance of selecting the right features for model performance and how features and labels work together to make predictions. The video concludes with a brief mention of the next topic, data splitting.

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