Why Learn Keras – Reasons Why Choose Keras

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.

Why Learn Keras?

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.

Features of Keras

Let us see some of the features of keras that make you learn Keras.

1. Simple API

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.

2. Pythonic Nature

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.

3. Strong Backend Support

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.

4. Base for Innovations

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:

• Deepjazz: This is deep learning-driven jazz built using Keras and theano, available on github.
• Eclipse Picasso: It is a visualization tool that works with Keras checkpoints.
• Auto Keras: It is built upon Keras and used for machine learning model automation.

Reasons to Learn and Use Keras

• Keras allows us to switch between the backends as per the requirement of our applications. It acts as a wrapper that gives us the privilege to use either TensorFlow, theano, or any other framework.
• Keras is very easy and enjoyable to use. It uses great guiding principles like extensibility, python nativeness, and modularity.
• The ability of Keras to create the state of the art implementations of common deep neural networks. These are fast and it is easy to get them running using Keras.
• Being Keras user, you will be more faster and productive, you will have the ability to try more ideas.
• Keras provides Multi-GPU and strong distributed support. We can run our deep learning models on large GPU clusters.
• We can deploy Keras deep learning models on multiple platforms. For example, We can deploy in the browser using tensorflow.js, on the server using either TensorFlow serving or using Node.js runtime. On mobile devices i.e in android or IOS, we can deploy using TensorFlow Lite.
• Keras has a large ecosystem of products to support your deep learning development. Some of the popular products are Tensorflow Cloud, Keras Tuner, Tensorflow Lite,Tensorflow.js, and Tensorflow Model Optimization.

Other Useful Keras Features

1. Developer Experience

Keras uses best practices to reduce computation loads. Using Keras, developers have to write as minimum code as possible. It is very flexible too because the integration of Keras with backend frameworks is very deep.

2. Industry and Research Adaptation

Keras is adapted widely in research communities and industries. Many big companies rely on Keras, including Netflix, Uber, and Instacart. Startups with deep learning applications prefer to use Keras over other frameworks. Many researchers and scholars mention Keras in their research papers. Keras is also adapted to big science research organizations like NASA.

Now when you have learnt Keras features and reasons to learn keras, Do not forget to Install keras to work on the same.

Summary

This article explains the need, importance, and necessity to learn Keras. It sequentially describes the positives that Keras provides, the reasons to use Keras, and its important features. It describes the positives like backend support, the basis of innovation, and the simplicity of Keras API.
This also explains the non-technical features like user experience and community support.