Machine Learning Concepts and Data Preparation

Structured Data

Data organized in a defined format, typically in tables with rows and columns.

Unstructured Data

Data that does not have a predefined format and is often text-heavy or includes multimedia.

Feature Matrix

A representation of independent variables in a dataset, usually denoted as X.

Label Vector

A representation of dependent variables or outcomes in a dataset, typically denoted as y.

One Hot Encoding

A technique to convert categorical variables into a binary format, where each category is represented as a single binary column.

Training Set

A subset of data used to train a model, allowing it to learn patterns and make predictions.

Testing Set

A subset of data used to evaluate the performance and accuracy of a trained model.

Data Preparation Steps

Procedures such as loading datasets, handling categorical variables, and scaling features.

Independent Variables

Predictor variables that influence the outcome in a dataset.

Dependent Variables

Outcome variables that are predicted based on the independent variables.

Missing Values

Data entries that