Deep learning is a branch of machine learning that uses neural networks with multiple layers to learn useful patterns from data. This lesson introduces what makes a model “deep,” how layered representations work, and how deep learning differs from traditional feature engineering.
Deep learning uses multilayered neural networks for tasks such as classification, regression, and representation learning. A network consists of connected computational units called artificial neurons, arranged into layers. Connections have adjustable weights that influence how signals pass through the network.
All flashcards
What is deep learning?
A class of machine-learning methods that uses multilayered neural networks to transform data and learn representations or produce outputs.
What is a layered representation?
A sequence of representations in which each layer transforms information, often building from simple patterns toward more abstract features.
How does deep learning differ from hand-crafted feature engineering?
Deep-learning models learn useful features from data, whereas feature engineering relies more on people to design or select features.
What is the credit assignment path?
The chain of transformations from input to output along which learning signals can be assigned to network parameters.
Does adding layers always improve a model?
No. Extra layers can help learn hierarchical features, but depth alone does not guarantee better performance.
Quiz questions
What operation is characteristic of convolutional neural networks?Answer: Convolutions that detect local patterns in data.
What is a key purpose of long short-term memory networks?Answer: Managing information over long sequences.
What does backpropagation efficiently compute during neural-network training?Answer: How parameter changes affect the output, using the chain rule.
What is data poisoning in machine learning?Answer: Inserting misleading or malicious examples into training data.
What does the universal approximation theorem establish, broadly?Answer: Certain networks can approximate broad classes of functions under specified assumptions.
Based on the Wikipedia article Deep learning, licensed CC BY-SA 4.0. Adapted into a summary, flashcards and quizzes.