Embedding

Vector Search

Vector search is a retrieval method that finds items by comparing the numerical similarity of their vector embeddings rather than matching exact keywords.

Semantic Search

Semantic search is an information retrieval approach that ranks results by contextual meaning and user intent rather than by exact keyword matches.

Haystack

Haystack is an open-source Python framework by deepset for building production-grade search and question-answering systems, including retrieval-augmented gener…

Unsupervised Learning

Unsupervised learning is a machine learning approach in which a model finds patterns, structure, or groupings in data without being given labeled outputs.

Self-Supervised Learning

Self-supervised learning is a machine learning technique in which a model generates its own supervisory labels from unlabeled data, learning by predicting hidd…

Attention Mechanism

The attention mechanism is a neural network technique that allows a model to dynamically weigh the importance of different parts of its input when producing ea…

Tokenization

Tokenization is the process of breaking text into smaller units, called tokens, that a language model can process — typically words, subwords, or characters.

Embedding

An embedding is a numeric vector representation of data — such as text, images, or audio — designed so that items with similar meaning or content are positione…

Feature Engineering

Feature engineering is the process of using domain knowledge to select, transform, and create the input variables (features) that a machine learning model is t…

Word2Vec

Word2Vec is a family of neural network-based techniques, introduced by Google researchers in 2013, that learn dense vector representations (word embeddings) of…

GloVe

GloVe (Global Vectors for Word Representation) is a word embedding technique, developed at Stanford, that learns dense vector representations of words by facto…

Embedding vs Referencing

Understand the core MongoDB modeling trade-off between embedding related data inside a document and referencing it via a separate collection.

Struct and Interface Embedding in Go

Understand how Go uses struct and interface embedding to compose behavior instead of using inheritance.

How Do You Design Document Schemas in MongoDB?

MongoDB document schema design means choosing, for each relationship in your data, whether to embed related data inside a single document or reference it from…