India, April 23 -- If you hear the word TensorFlow in a discussion about machine learning, it may feel like a brand name, like the Dodge Hemi or Ford Powerstroke Diesel. But imaginative pickup engine names are an apt analogy because TensorFlow, a mathematic computational framework that supports a number of deep neural network protocols, has an opportunity to be the engine behind analyzing data and algorithms associated with chatbots, smart devices and other cloud services.
TensorFlow has become popular because its tensors -- multidimensional arrays of data meant to represent a set of variables -- can represent a set of features for a product, service or event. The tensors carry a set of data observations through epochs, nodes that apply a ...