Introduction to Machine Learning

A set of flashcards based on lecture notes about machine learning concepts, definitions, and terminology.

Data

Facts and statistics collected together for reference or analysis.

Science

A systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.

Data Science

The field that involves using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

Descriptive Analytics

Analyzes historical data to answer the question 'What happened?'

Diagnostic Analytics

Analyzes data to understand why something happened.

Predictive Analytics

Uses data to predict future outcomes and answer the question 'What will happen next?'

Prescriptive Analytics

Suggests the best course of action based on predictive analytics.

Predictive Model

A model built to predict an unknown outcome based on historical data.

Machine Learning

The study of using a computer to automatically find patterns in data.

Classification

A type of predictive modeling technique used when the target attribute is a category.

Regression

A type of predictive modeling technique that predicts a target attribute which is a real number.

Clustering

A technique for grouping data points based on their properties without predefined categories.

Dimensionality Reduction

The process of reducing the number of input variables in a dataset.

Model Evaluation

The process of assessing the performance of a predictive model using various metrics.

Scikit-learn

A popular open-source machine learning library for Python, featuring a range of supervised and unsupervised learning algorithms.