8 Introduction to Machine Learning Free Online FlashCards

What does machine learning use data to do?

Machine learning uses data to build models that identify patterns and produce predictions or descriptions.

In a dataset, what are examples and features?

An example is a row in a dataset; its features are the input columns describing it.

How does supervised learning learn?

Supervised learning uses examples with known labels to predict labels for new examples.

What does a classification model predict?

Classification predicts a category, such as whether an email is spam.

What caution applies to clusters found by an algorithm?

Clustering can group customers with similar purchasing patterns, but the resulting groups are not automatically meaningful categories; they require interpretation.

What happens during model training?

During training, an algorithm fits a model using training data, for example by adjusting parameters to reduce prediction errors.

What is a test set used for?

A test set contains separate examples used to estimate how well a fitted model performs on data it has not seen.

What is data leakage?

Data leakage occurs when training features contain information that would not actually be available when making a prediction.

What does precision measure?

Precision is the fraction of predicted positives that are truly positive: $\frac{TP}{TP + FP}$.

What is a label in supervised learning?

A label is the value a supervised model is meant to predict for an example.

What does a regression model predict?

Regression predicts a numerical value, such as a home's sale price.

What distinguishes unsupervised learning?

Unsupervised learning searches for structure in features when there are no target labels.