TensorFlow is an interface for expressing machine learning algorithms, and it's an implementation for executing such algorithms. The TensorFlow computation can be expressed with little or no change on a wide variety of heterogeneous systems, such as mobile phones, tablets, and large-scale distributed systems of hundreds of machines. It is flexible and can express a wide variety of algorithms, such as training and inference algorithms for deep neural network models. It is also used for deploying machine learning systems into production across many areas, such as speech recognition, computer vision, robotics, information retrieval, natural language processing, geographic information extraction, and so on.

The application of tensors and their networks is a relatively new (but fast-evolving) approach in machine learning. Tensors, if you recall your algebra classes, are simply n-dimensional data arrays (so a scalar is a 0th order tensor, a vector is 1st order, and a matrix...