TensorFlow is an open-source software library from Google. It was meant for dataflow programming across a range of tasks. It is a symbolic math library, and is largely used for machine learning applications such as neural networks. Originally it was developed by the Google Brain team for internal Google use. As the AI research community got more and more collaborative, TensorFlow was released under the Apache 2.0 open source license.


Before proceeding with the internals, let us have a look at an example solution using TensorFlow. That can give us an idea of the power packed into this library.

Classification is one of the frequent problems we work in AI. Typically we have a set of inputs that have to be classified into different categories. We can use TensorFlow to train a model for this task. Let us see how.

Basic Concepts

TensorFlow and its component Keras, are vastly used in implementing Deep Learning algorithms. Like most machine learning libraries, TensorFlow is "concept-heavy and code-lite". The syntax is not very difficult to learn. But its concepts are very important.