developer-roadmap/roadmaps/machine-learning/content/data-loading@bIhGv4886V4RWJD3tX0a0.md

Data Loading in Scikit-learn

Data loading in Scikit-learn refers to the process of importing datasets into a format that can be used for machine learning tasks. This involves reading data from various sources, such as CSV files, databases, or even directly from NumPy arrays, and structuring it into a format that Scikit-learn's algorithms can understand, typically NumPy arrays or Pandas DataFrames. The loaded data is then usually split into features (independent variables) and a target variable (dependent variable) for training and evaluating machine learning models.

Visit the following resources to learn more:

• @official@Dataset loading utilities
• @video@Scikit-Learn Full Crash Course - Python Machine Learning