What is the full form of KERAS in Python?

KERAS means horn in Greek. It is an open-source software library under Python that runs on top of Tensorflow, Theano and CNTK Backend. It was developed by ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System). It has two types of e data structures. These are layers and models
Features
It has the user-friendly framework
Concept of Deep learning models
It supports multiple platforms and backends.
Keras also supports both CPU and GPU.

Python is a programming language which is being learnt and used by many coders because of its great flexibility and convenience. In Python architecture we have a powerful and easy-to-use free open source library. This library is used for developing and evaluating deep learning models. The programmer can call these library functions in its code easily and they form a part of the neural network models that the programmer uses for an effective coding and software solution.
The literal meaning of Keras, which is a Greek word, is horn. This library was initially developed as a part of the research project - ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System). Later it became very useful in neural network coding and today it is the integral part of the Python programming. Keras library is efficiently used along with the computation libraries Theano and TensorFlow and helps the coder to define a neural network in a few lines of Keras codes.
For using Keras one has to have Python 2 or 3 installed and configured, SciPy (including NumPy) installed and configured, and Keras and a backend (Theano or TensorFlow) installed and configured in one's system for working in the Keras environment under the overall Python architecture.

KERAS is not an abbreviation. It is a greek word. The meaning of this word is horn in that language. This word was found first in Odyssey which is a Greek epic poem written by Homer about the long journey of a man named Odysseus. In computer applications, it is a high-end application programming interface (API). This was developed for the first time as a part of the research project, Open-ended Neuro-Electronic Intelligent Robot Operating System ( ONEIROS). When neural networks are developed with Python, Keras is being used as a framework for the development of the same.
It is easy to use and useful to build deep learning systems. It will support some network architectures like multi-input or multi-output models, layer sharing, model sharing, and so on. It is front end coding written in Python This coding will run with other backends like TensorFlow, Theano and Microsoft Cognitive Toolkit (CNTK)

KERAS is the high level of API which is embedded in the Tensor Flow. It is being used to be user friendly, modular extendable and this can help us while working in Python. It was initially designed to ease the working process of human being and not for machine.
Our aim is to reduce the cognitive load with the application of KERAS. The chief reason to use KERAS originate from its guiding principles of user friendly apart from its ease of learning. It consists of synthesis of five engines such as Tensor Flow, CNTK, Theano, MX Net and Plaid ML. Moreover, it is supported by Google, Microsoft, Amazon, Apple, Uber and others.
KERAS would supply seven common deep learning data sets including Cifar 10 and Cifar 100 for colour images, PMB movie reviews, MNIST images etc.