This article is the spotlight on the need for python deep learning library, Keras. Keras offers a uniform face for various deep learning frameworks including Tensorflow, Theano, and MXNet. Let us see why you should choose and learn keras now.
Keras makes deep learning accessible and local on your computer.It also acts as a frontend for other big cloud providers. It is the most voted recommendation for beginners who want to start their journey in machine learning. It provides a minimal approach to run neural networks. This allows students to learn complex features from input data sequentially.
Let us see some of the features of keras that make you learn Keras.
Keras is the most easy to use the library for machine learning for beginners. Being simple helps it to bring machine learning from imaginations to reality. It provides an infrastructure that can be learned in very less time. Using Keras, you will be able to stack layers like experts.
Python is the most popular library for machine learning and Data Science. The compatibility with python allows Keras to have many useful features. Writing less code, easy to debug, easy to deploy, extensibility is due to the support of Keras with python 2.7 and python 3.6.
Keras being a high-level API provides support for multiple popular and powerful backend frameworks. Tensorflow, theano, CNTK are very dominant for backend computations and Keras supports all of them.
The importance of Keras leads to many other innovative tools to explore deep learning. These tools are built on top of Keras making Keras as the base. The following tools are:
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