Keras 简明教程

Keras - Introduction

深度学习是机器学习框架的一个主要子领域。机器学习是对算法设计的学习，灵感来自人脑模型。深度学习在数据科学领域越来越流行，如机器人技术、人工智能 (AI)、音频和视频识别以及图像识别。人工神经网络是深度学习方法的核心。深度学习受到 Theano、TensorFlow、Caffe、Mxnet 等各种库的支持，Keras 是最强大和最易于使用的 Python 库之一，它建立在 TensorFlow、Theano 等流行深度学习库之上，用于创建深度学习模型。

Deep learning is one of the major subfield of machine learning framework. Machine learning is the study of design of algorithms, inspired from the model of human brain. Deep learning is becoming more popular in data science fields like robotics, artificial intelligence(AI), audio & video recognition and image recognition. Artificial neural network is the core of deep learning methodologies. Deep learning is supported by various libraries such as Theano, TensorFlow, Caffe, Mxnet etc., Keras is one of the most powerful and easy to use python library, which is built on top of popular deep learning libraries like TensorFlow, Theano, etc., for creating deep learning models.

Overview of Keras

Keras 运行于 Tensorflow、Theano 或 Cognitive Tookit (CNTK) 等开源机器库之上。Theano 是一个用于快速数值计算任务的 python 库。TensorFlow 是用于创建神经网络和深度学习模型的最著名的符号数学库。TensorFlow 非常灵活，最主要的优点是分布式计算。CNTK 是 Microsoft 开发的深度学习框架。它使用 Python、C#、C++ 等库或独立的机器学习工具包。Theano 和 TensorFlow 是非常强大的库，但对于创建神经网络来说很难理解。

Keras runs on top of open source machine libraries like TensorFlow, Theano or Cognitive Toolkit (CNTK). Theano is a python library used for fast numerical computation tasks. TensorFlow is the most famous symbolic math library used for creating neural networks and deep learning models. TensorFlow is very flexible and the primary benefit is distributed computing. CNTK is deep learning framework developed by Microsoft. It uses libraries such as Python, C#, C++ or standalone machine learning toolkits. Theano and TensorFlow are very powerful libraries but difficult to understand for creating neural networks.

Keras 基于极小的结构，提供了一种干净且简单的方式来创建基于 TensorFlow 或 Theano 的深度学习模型。Keras 旨在快速定义深度学习模型。好吧，Keras 是深度学习应用程序的最佳选择。

Keras is based on minimal structure that provides a clean and easy way to create deep learning models based on TensorFlow or Theano. Keras is designed to quickly define deep learning models. Well, Keras is an optimal choice for deep learning applications.

Features

Keras 采用各种优化技术，使高级神经网络 API 变得更加简单、高效。它支持以下功能：

Keras leverages various optimization techniques to make high level neural network API easier and more performant. It supports the following features −

  1. Consistent, simple and extensible API.

  2. Minimal structure - easy to achieve the result without any frills.

  3. It supports multiple platforms and backends.

  4. It is user friendly framework which runs on both CPU and GPU.

  5. Highly scalability of computation.

Benefits

Keras 是一个非常强大且动态的框架，具有以下优点：

Keras is highly powerful and dynamic framework and comes up with the following advantages −

  1. Larger community support.

  2. Easy to test.

  3. Keras neural networks are written in Python which makes things simpler.

  4. Keras supports both convolution and recurrent networks.

  5. Deep learning models are discrete components, so that, you can combine into many ways.