Tensor operations refer to mathematical manipulations involving tensors, which are multi-dimensional arrays of numbers. These operations include addition, subtraction, and multiplication, allowing for the combination and transformation of data in various dimensions. Tensors can represent a wide range of data types, from scalars (0D) to vectors (1D) and matrices (2D), extending to higher dimensions. In machine learning and deep learning, tensor operations are crucial for processing and analyzing large datasets. Frameworks like TensorFlow and PyTorch provide built-in functions to perform these operations efficiently, enabling complex computations that drive model training and inference.