Keras is an open-source neural network library written in Python. It is designed to enable fast experimentation with deep neural networks and focuses on being user-friendly, modular, and extensible. With Keras, developers can easily build and train deep learning models, making it a popular choice for beginners and experienced machine learning practitioners alike. Its high-level API allows for quick prototyping and supports convolutional networks, recurrent networks, and a combination of the two.
PyPI Packages is a category that encompasses various Python packages available for use in different applications. Keras falls under this category as a widely-used Python package specifically tailored for deep learning tasks. It provides a simplified interface to complex neural network functionalities, making it easier for developers to implement deep learning models without diving too deep into the intricacies of neural network architecture.
Keras was founded in March 2015 by François Chollet as an open-source project. Its inception aimed to provide a user-friendly interface for building neural networks on top of popular deep learning libraries such as TensorFlow and Theano. Over time, Keras gained traction within the machine learning community due to its ease of use and flexibility.
In terms of current market share, Keras has established itself as one of the leading deep learning frameworks in the industry. Its seamless integration with TensorFlow, which has become the dominant framework for deep learning, has contributed to its widespread adoption. While facing competition from other deep learning libraries, Keras continues to grow its user base and is forecasted to maintain and potentially increase its market share in the future. As the demand for deep learning solutions continues to rise, Keras is poised to remain a key player in the field of neural network development.
