Tensor

Gold definitionUpdated Apr 2, 2026

Definition

A tensor is a multi-dimensional array used to represent data in machine learning, generalizing scalars, vectors, and matrices. It serves as the fundamental data structure for inputs, outputs, and model parameters, enabling complex computations in deep learning frameworks.

At a glance

Executive summary

Tensors are the core data structures in AI, acting as multi-dimensional containers for all types of information, from images to model parameters. They are essential for deep learning frameworks to perform complex calculations efficiently and enable the training and deployment of AI models.

TL;DR

Tensors are like smart, multi-dimensional containers that hold all the numbers and data AI models use to learn and make decisions.

Key points

A multi-dimensional array that generalizes scalars, vectors, and matrices to represent diverse data.
Provides a universal, flexible data structure for all inputs, outputs, and parameters in machine learning models.
Used by machine learning engineers, AI researchers, and deep learning frameworks like TensorFlow and PyTorch.
More general and foundational than simpler data structures; it's the underlying representation for most numerical data in ML.
Foundational, but advanced tensor operations (e.g., tensor networks, tensor products for function approximation) are active areas for model efficiency and expressiveness.

Use cases

Image Processing: Representing images as 3D tensors (height, width, color channels) or 4D tensors (batch size, height, width, channels) for convolutional neural networks.
Natural Language Processing: Storing text data as 2D or 3D tensors, where each dimension might represent batch size, sequence length, and embedding dimension.
Reinforcement Learning: Representing environmental states, actions, and value functions as tensors for agents to learn optimal policies, as seen in the context of SPAN.
Scientific Computing: Handling large datasets in physics, chemistry, and neuroscience, where multi-dimensional arrays are natural for simulations and experimental data analysis.

Also known as

Multi-dimensional array, N-dimensional array, ND-array