What is the Keras framework in Python?

What is the Keras framework in Python?

Keras is a high-level API for building deep learning models. It is implemented based on the Python programming language and is based on open source software libraries such as TensorFlow, Theano or CNTK. It provides a simple and fast way to create deep learning models. method.

Keras was created by Francois Chollet and first released in 2015. Its design goal is to make deep learning technology easier to use, lower the threshold for deep learning frameworks, and help enable more developers Participants participate in research and application in the field of deep learning.

The main features of Keras

1. High degree of modularity

The design goal of Keras is to make model organization simpler and easier to understand. It provides a set of modular API can quickly create various model structures and allow users to customize and add new modules.

2. Easy to extend

Keras allows you to define and extend your own network layers, loss functions, evaluation metrics and training processes. It also provides a set of APIs to switch between different backends such as TensorFlow, Theano and CNTK.

3. Simplicity

Keras is written in Python, an easy-to-learn programming language, which makes Keras code easy to read and understand. Keras is an easier-to-use framework compared to other deep learning frameworks.

4. High degree of portability

Keras can work normally on different types of computing platforms, including hardware devices such as CPU, GPU and TPU, and also supports multiple operating systems. Including Windows, Linux and Mac, etc.

Applications of Keras

Keras can be used for various types of deep learning tasks, including image classification, image segmentation, speech recognition, natural language processing, etc.

In image classification tasks, Keras can be used to train convolutional neural networks (CNN), recurrent neural networks (RNN) and other models, and can perform well on MNIST, CIFAR-10, Imagenet and other data sets.

In natural language processing tasks, Keras can be used to train sequence models, such as LSTM, GRU and other models, and achieve excellent performance in tasks such as text classification and sequence annotation.

In general, Keras is a very popular deep learning framework that can quickly build and train various models. It is also a good choice for getting started with deep learning.

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