Caffe2 简明教程
Caffe2 Tutorial
在本教程中,我们将学习如何使用名为 Caffe2 (快速特征嵌入的卷积架构)的深度学习框架。此外,我们将了解传统机器学习与深度学习之间的差异,Caffe2 与 Caffe 相比的新功能,以及 Caffe2 的安装说明。
In this tutorial, we will learn how to use a deep learning framework named Caffe2 (Convolutional Architecture for Fast Feature Embedding). Moreover, we will understand the difference between traditional machine learning and deep learning, what are the new features in Caffe2 as compared to Caffe and the installation instructions for Caffe2.
Audience
本教程专为那些热衷于学习使用模块化且可扩展的深度学习框架 Caffe2 为解决问题创建模型和新算法的人员设计。此外,它还适用于那些渴望借助云中的图形处理单元 (GPU) 或在移动设备上使用跨平台库来扩展其作品的程序员。
This tutorial is designed for those who have keen interest in learning about creating models and new algorithms for solving problems with the help of a modular and scalable deep learning framework, Caffe2. Furthermore, it is for the programmers who are eager to bring their creations to scale with the help of graphics processing units (GPUs) in the cloud or to common people on mobile with cross - platform libraries.
Prerequisites
在继续学习本教程之前,我们假定您已经具备有关深度学习框架、机器学习库 PyTorch 以及 C++、Python 和 MATLAB 等编程语言的先验知识。如果您不熟悉前面提到的任何技术,则可以在开始本教程之前参考相应的教程。
Before you proceed with this tutorial, we assume that you have prior knowledge about deep learning framework, machine learning library PyTorch and programming languages such as C++, Python and MATLAB. If you are novice to any of the technologies mentioned before, you can refer to the respective tutorials before beginning with this tutorial.