Programming model and Basic concepts

Each computation in TensorFlow describes a directed graph that’s composed of nodes and edges where nodes are operations/ functions and edges are input and output overflows and those functions.  

• Inputs/ Outputs in TensorFlow are called Tensor. Tensor is nothing but a multi-dimensional array for which the underpinning element type is specified at the graph construction time.
• The client program that uses TensorFlow generates data- flow graphs using endorsed programming languages (C or Python).
• An operation is a function that has a name and represents an abstract computation. An operation can have attributes that should be generated and handed at the time of graph construction.
• One frequent application of attributes is to fabricate operation polymorphic.
• The kernel is the implementation of an operation on a specific device.
• The client program interacts with TensorFlow system inflow by creating sessions. The session interface has extended styles to generate a computation graph and its reinforcement run() method which computes output of individual node in prosecution graph by providing needed inputs.
• In utmost of the machine learning tasks computation graphs implemented multifold times and utmost of the ordinary tensors don’t survive after unattached accomplishment that’s why TensorFlow has variables.
• Variable is a special kind of operation that returns a handle to a variable Tensor which can survive during multiple prosecutions of the graph.
• Trainable Parameters like weights, biases are reposited in Tensors held in variables.

Prerequisite: Introduction to TensorFlow

TensorFlow is an end-to-end open-source platform for machine learning developed by Google with many enthusiastic open-source contributors. TensorFlow is scalable and flexible to run on data centers as well as mobile phones. It can run on single-machine as well as multiple-machine in a distributed setting. In this article, we will explore the secret behind the extreme flexibility and scalability of TensorFlow.