AI Glossary: Letter "E"

Early Stopping is a regularization technique that halts a model's training process when its performance on a separate validation dataset stops improving, even if the training loss continues to decrease.

Edge AI is the practice of running machine learning models and processing data directly on physical devices at the "edge" of the network (like smartphones, laptops, or IoT devices), rather than relying on centralized cloud servers.

An Embedding is a representation of real-world data (words, sentences, images, user profiles) as high-dimensional vectors of real numbers. Embeddings place semantically similar concepts close to each other in vector space.

Embedding Dimension is the coordinate length of the vector used to represent data items in a latent space (e.g. OpenAI's text-embedding-3-small uses 1536 dimensions). It determines the detail capacity of the semantic space.

Ensemble Methods are machine learning techniques that combine predictions from multiple individual models to create a single, more robust prediction. Examples include bagging, boosting, and stacking.

An Epoch is a single complete pass of the entire training dataset through a machine learning model. Training typically consists of many epochs to allow the network to refine weights and biases based on multiple passes over the data.

Euclidean Distance is a mathematical metric measuring the straight-line distance between two coordinates in Euclidean space. In vector search, it is used to measure the similarity between two embedding vectors.

Explainable AI (XAI) is a suite of processes and methods that allow human users to comprehend and trust the results and outputs generated by machine learning algorithms. It aims to demystify the "black box" of deep neural networks.

The Exploding Gradient Problem is an error during backpropagation training where gradients accumulate, resulting in unstable, massive parameter updates that prevent model weights from converging.