How to Build a Model in Keras?

Understanding Keras

Keras is a high-level, user-friendly API used for building and training neural networks. It is designed to be user-friendly, modular, and easy to extend. Keras allows you to build, train, and deploy deep learning models with minimal code. It provides a high-level API that is intuitive and easy to use, making it ideal for beginners and experts alike....

History of Keras

Keras was developed by Google engineer named François Chollet. It was developed as part of research project called ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System) and it was released in March 2015. The goal of Keras was to enable fast experimentation with deep neural networks. Later, Keras was incorporated into TensorFlow as ‘tf.keras’, which made it an official high-level API of TensorFlow while still supporting its standalone version that could interface with other computational backends like Theano or CNTK....

Key Features of Keras Library

Simplicity...

How to Build a Model in Keras?

Keras provides two main ways to build models:...

Building Model using Sequential API

Here’s how you can define a Sequential model:...

Building Model using Functional API

The Functional API allows more flexibility in creating complex architectures. You can create models with shared layers, multiple inputs/outputs, and skip connections....

Applications of Keras

Keras is commonly used for:...

Conclusion

Keras has revolutionized deep learning by providing an accessible and productive interface. Whether you’re a researcher, engineer, or ML practitioner, Keras simplifies the process of building and training neural networks. It also allows fast and easy prototyping and can run easily on CPU and GPU. Keras turns idea into reality....

FAQs on Keras

What is Keras used for?...