Vectors

Overview

In mathematics and computer science, vectors are mathematical objects that represent both magnitude and direction, often visualized as arrows in a multi-dimensional space. In the context of machine learning and AI, vectors are typically used to represent data points, features, or embeddings as ordered lists of numbers. These numerical representations enable mathematical operations and computations on the data, forming the basis for many algorithms and machine learning algorithms.

Key Characteristics

• Dimensionality: Number of components in the vector
• Direction: Orientation in space
• Magnitude: Length or size of the vector
• Components: Individual numerical values

Common Applications

• Feature representation in machine learning
• Text embeddings in NLP
• Image representation in computer vision
• Data point representation in clustering
• Similarity calculations in search

Related Concepts

• Embedding
• Vectorization
• Vector Database
• Vector Search
• Machine Learning
• Neural Network