Explanation of "Neural Network"
Definition: A "neural network" is a system that can learn and make decisions by mimicking how the human brain works. In simple terms, it is made up of units (like neurons in the brain) that connect and communicate with each other to process information.
Advanced Usage:
In more advanced discussions, "neural networks" can refer to specific types of architectures in AI, such as: - Convolutional Neural Networks (CNNs): Often used for image processing. - Recurrent Neural Networks (RNNs): Used for processing sequences, like time series data or text.
Word Variants:
Neural (adjective): Relating to nerves or the nervous system. Example: "Neural activity increases during learning."
Network (noun): A group of interconnected things. Example: "The internet is a vast network of computers."
Different Meanings:
In biology, a "neural network" refers to the actual network of neurons in a living organism's brain or nervous system.
In technology, it refers specifically to the computer models that simulate this biological process.
Synonyms:
Artificial Neural Network (ANN): A common term in AI referring to neural networks used in computing.
Deep Learning Model: Often used interchangeably with neural networks, especially deep neural networks that have many layers.
Idioms and Phrasal Verbs:
Summary:
In summary, a neural network is a way for computers to learn and make decisions like humans do, using interconnected units that process information.