AI GlossaryGradient DescentENTRY — Machine Learning
[Machine Learning]
Gradient Descent.
An optimization algorithm that iteratively adjusts model parameters to minimize the loss function.
In-depth explanation
01Gradient descent calculates the gradient (slope) of the loss function with respect to each parameter and takes steps in the direction that reduces the loss. Variants include batch gradient descent (uses all data), stochastic gradient descent (uses one sample), and mini-batch gradient descent (uses small batches). Learning rate controls step size.
Examples
02EX. 01
Training neural networks
EX. 02
Fitting linear regression
More in Machine Learning
0301ClassificationPredicting which category or class an input belongs to from a set of predefined categories.02Cross-ValidationA technique to evaluate model performance by training and testing on different subsets of data.03Ensemble LearningCombining multiple models to produce better predictions than any single model.04FeatureAn individual measurable property or characteristic of data used as input to a machine learning model.05Feature EngineeringThe process of using domain knowledge to create new features that improve model performance.06HyperparameterConfiguration settings set before training that control the learning process, not learned from data.
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