In mathematics, a tensor is an algebraic object that describes a linear mapping from one set of algebraic objects to another. According to Ars Technica, “Basically, a tensor is a matrix of equations, instead of a matrix of pure numbers. Tensor mathematics is the manipulation of these equation matrices as a method of solving ALL of the involved equations.”
Industry starting with google have introduced open source libraries and frameworks that support development of machine learning applications. Deep learning relies on neural networks—systems that approximate the web of neurons in the human brain.
A framework is a toolbox for creating, training, and validating deep-learning neural networks. Using a high-level programming API, it hides the complexities of the underlying algorithms to greatly simplify and speed up development. Like deep learning, frameworks are evolving rapidly.
Currently, the most popular framework is TensorFlow, an open-source software library created and supported by Google. TensorFlow is a way of building and running these neural networks—both at the training stage and the execution stage. It’s a set of software libraries—a bunch of code—that you can slip into any application so that it too can learn tasks like image recognition, speech recognition, and language translation. The name TensorFlow derives from the operations that such neural networks perform on multidimensional data arrays, which are referred to as tensors.
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