Before diving into TensorFlow.js itself, we need to be familiar with the idea of operation graphs, or calculation graphs, which are common constructs that we'll use to build machine learning models alongside modern frameworks such as TensorFlow. In these frameworks, the data is represented as a tensor. A tensor is a data structure that represents an arbitrary dimensional array. Those of you who have used the NumPy library in Python may already be familiar with this concept. In NumPy, ndarray is commonly used to display various kinds of data in machine learning, such as images and audio, regardless of whether it's structured or unstructured.
Modern machine learning frameworks, including TensorFlow, illustrates the fact that machine learning models are operation graphs of tensors. An operation graph is defined as a chain that's used for the manipulation...