If you have worked on a Deep Learning model, you probably already know what TensorFlow is. It is an Open Source python library and is used for numerical computation and large-scale machine learning. TensorFlow bundles together a slew of machine learning and deep learning (or neural networking) models and algorithms and makes them useful by way of a common metaphor. It uses Python to provide a convenient front-end API for building applications with the framework, while executing those applications in high-performance C++.
Internally, it uses two data structures namely Tensors and Dataflow graph for its fundamental operations which relies on graph concepts.
Read this article to understand how TensorFlow uses Graph concepts
This is a companion discussion topic for the original entry at http://iq.opengenus.org/how-tensorflow-uses-graph-data-structure-concepts/