Category: L

Deep Learning is a specialized form of Machine Learning and a crucial part of artificial intelligence. It uses artificial neural networks with multiple layers, hence

A Large Language Model, or LLM, is a special kind of artificial neural network created to grasp and create natural language. With the help of

A label refers to the “answer” part of the examples used in supervised machine learning. It also denotes the portion of the training data that

This regularization penalizes weights proportionally to their squares. L2 regularization brings high-positive and low-negative outlier weights closer to 0 but not quite to 0. Features

A regularization that penalizes weights by their sum of absolute values. L1 regularization reduces irrelevant feature weights to 0. Zero-weighted features are eliminated from the

A loss function that determines the exact difference between label values and model predictions. L1 loss is less outlier-sensitive than L2. Applications of L1 Loss

A regularization that penalizes a model’s total nonzero weights. A model with L1 nonzero weights is penalized more than one with L0. L0 regularization is