May 2024
Intermediate to advanced
389 pages
6h 49m
Chinese
Content preview from 深度学习：核心原理与案例分析Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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第4章 TensorFlow入门实战
本章介绍一个现阶段使用最广泛的深层学习框架——TensorFlow。因为TensorFlow所拥有的社区支持度日益增长，所以使用它来构建复杂的深度学习应用程序是我们的不二选择。从TensorFlow网站我们可以看到：
TensorFlow是一个使用数据流图进行数值计算的开源软件库。图中的节点代表数学运算，而图中的边则代表在这些节点之间传递的多维数组（张量）。借助这种灵活的架构，你可以通过一个API将计算工作部署到台式机、服务器或移动设备中的一个或多个CPU或GPU上。TensorFlow 最初是由Google Brain团队（隶属于Google机器智能研究部门）的研究人员和工程师开发的，旨在用于进行机器学习和深度神经网络研究。该系统具有很好的通用性，还可以应用于众多其他领域。
本章将介绍以下内容。
- 安装TensorFlow。
- TensorFlow运行环境。
- 计算图。
- TensorFlow中的数据类型、变量和占位符。
- 获取TensorFlow的输出。
- TensorBoard——可视化学习过程。
4.1 安装TensorFlow
TensorFlow有两种版本可以安装，分别是CPU版和GPU版。本书将使用GPU版。
4.1.1 在Ubuntu 16.04系统上安装GPU版的TensorFlow
在安装GPU版的TensorFlow之前，首先需要安装最新版的NVIDIA驱动程序，因为现阶段GPU版的TensorFlow只支持CUDA。接下来将会带领读者一步步地安装NVIDIA驱动程序和CUDA8驱动程序。
1．安装NVIDIA驱动程序和CUDA 8
首先需要安装正确的NVIDIA驱动程序。这里以GeForce GTX 960M GPU为例，因此会安装nvidia-375（如果读者使用的是其他版本，请通过NVIDIA官网来找到适合你的驱动程序）。如果你想确认你的GPU型号，可以在终端中使用如下命令。 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.