Which of the frameworks uses the TensorFlow MXNet theano and CNTK as its backend?

This is a minimalistic Python-based library that can be run on top of TensorFlow, Theano, or CNTK. It was developed by a Google engineer, Francois Chollet, in order to facilitate rapid experimentation.

Which one of the following libraries use computations graph of deep learning TensorFlow theano torch Caffe?

Answer: Tensor Flow (Google) is the correct answer to this question. Its aim is oriented to artificial neural networks and research on computer technology. Since late 2015 the library has been officially open-sourced on GitHub.

Why do the deep learning frameworks use computation graphs?

Computational Graphs: How This very simple algorithm allows us to set up algorithms to train any deep neural network. This is exactly what any deep learning framework is supposed to do; they are in reality automatic differentiation libraries more than anything else.

What is the difference between theano and TensorFlow?

Theano is a fully python based library, which means it has to be used with the only python. This library will work with the python language and depends on python programming to be implemented. TensorFlow is a C++ and python based library that means it can be used in both the C++ and python programming.

Why TensorFlow is proper library for deep learning?

TensorFlow is an open source library for fast numerical computing. Unlike other numerical libraries intended for use in Deep Learning like Theano, TensorFlow was designed for use both in research and development and in production systems, not least RankBrain in Google search and the fun DeepDream project.

What is TensorFlow and why it is used?

It is an open source artificial intelligence library, using data flow graphs to build models. It allows developers to create large-scale neural networks with many layers. TensorFlow is mainly used for: Classification, Perception, Understanding, Discovering, Prediction and Creation.