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.
What is Keras?
Keras is an open-source deep-learning framework that gained attention due to its user-friendly interface. Keras offers ease of use, flexibility, and the ability to run seamlessly on top of TensorFlow. In this article, we are going to provide a comprehensive overview of Keras.
Table of Content
- Understanding Keras
- History of Keras
- Key Features of Keras Library
- How to Build a Model in Keras?
- Building Model using Sequential API
- Building Model using Functional API
- Applications of Keras