Eel

EEL (Entity Embedding Layer) is a neural network component used to convert categorical data, like words or labels, into numerical vectors that computers can process. Instead of representing categories as simple numbers, EEL assigns each one a unique, fixed-length vector that captures its relationships and similarities with others. This helps the model understand and analyze complex patterns in data, such as language or user preferences. EEL is efficient and improves learning by enabling models to process categorical variables more effectively, making it ideal for tasks like natural language processing, recommendation systems, and classification problems.