What is a Dataset

In Machine Learning, a dataset is just a collection of data that we use to train and test our models.

Think of it like an Excel sheet:

• Rows → each row is one data point (called a sample).
• Columns → each column contains information about that sample.

Features (Inputs)

• Features are the independent variables — the input data we provide to the ML model.
• They describe the properties of each sample.
• Example:
  • Age
  • Salary
  • Height
  • Exam scores Features are like the ingredients we give to a recipe.

Labels (Outputs / Targets)

• The label is what we want the model to predict.
• It is also called the dependent variable or target.
• Example:
  • Will the student pass or fail? (Yes/No)
  • Price of a house
  • Disease diagnosis (Positive/Negative)

Labels are like the final dish that we expect after cooking with the ingredients.

Example Dataset