A subset of artificial intelligence that enables systems to learn from data and improve over time without explicit programming.

Techniques that analyze historical data to make predictions about future events, crucial for anticipating user preferences in smart homes.

A residence equipped with devices that automate tasks and enhance convenience through connectivity and control via the internet.

A network of interconnected devices that communicate and exchange data, enabling automation and smart functionalities.

The use of technology to perform tasks with minimal human intervention, enhancing efficiency in smart home systems.

The process of gathering information from various sources, essential for training machine learning models.

Techniques used to clean and organize raw data before analysis, ensuring accuracy and relevance.

The process of choosing the most suitable machine learning algorithm for a specific problem or dataset.

Combining various components of a smart home system to work together seamlessly, often involving APIs and protocols.

Using machine learning to anticipate how users will interact with smart home devices based on historical data.

Principles guiding the responsible use of artificial intelligence, focusing on fairness, transparency, and user privacy.

The right of individuals to control their personal information and how it is used, particularly in smart home technologies.

A set of rules that allows different software applications to communicate, essential for integrating IoT devices.

Data that is free from errors and inconsistencies, crucial for accurate machine learning outcomes.

Information that is delivered immediately after collection, allowing for timely responses in smart home systems.

A process of making continuous enhancements based on feedback and testing results, vital for prototype development.

The means by which users interact with a device or application, focusing on usability and experience.

A mathematical model that enables computers to learn from data and make predictions or decisions.

An in-depth analysis of a specific instance or example, often used to illustrate concepts in real-world scenarios.

The graphical representation of data to identify trends and insights, aiding in data analysis.

The process of identifying and evaluating potential risks associated with a project, particularly in AI development.

An early sample or model of a product used to test concepts and functionalities before full-scale production.

Evaluating a product by testing it with real users to gather feedback and improve design.

A trained algorithm that can make predictions or decisions based on input data, essential for smart home systems.