How TensorFlow uses Graph data structure concepts?

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

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