January 2023
Intermediate to advanced
288 pages
6h 6m
Chinese
Content preview from 移动端AI与ML应用开发：基于iOS和Android
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18
|
第
1
章
像上训练了一个神经网络，让计算机找出每个诊断的决定因素。随着时间的推移，计算
机在能够诊断不同类型的糖尿病视网膜病变方面变得顶级好了！
1.3
在移动设备上构建和使用模型
在这里，你看到了一个非常简单的示例，说明如何从基于规则的编程过渡到 ML 以解决
问题。但是，如果你无法将解决方案交到用户手中，那么解决问题就没有多大用处，而
在运行 Android 或 iOS 的移动设备上使用 ML 模型，你就可以做到这一点！
这是一个复杂多变的情况，在本书中，我们将通过多种不同的方法让你更轻松地完成这
一任务。
例如，可能有一个交钥匙解决方案供你使用，现有模型能为你解决问题，你只想学习如
何做到这一点。我们将介绍人脸检测等场景，模型会为你检测图片中的人脸，并且你希
望将其集成到你的应用程序中。
此外，在很多场景中，你不需要从头开始构建模型、搞清楚架构以及经历漫长而费力的
训练。通常可以使用称为迁移学习的方法，你可以获取预先存在的模型并重新调整它们
的用途。例如，大型科技公司和顶尖大学的研究人员可以获得你可能无法获得的数据和
计算能力，他们已经用这些来构建模型了。他们已经与全世界分享了这些模型，因此这
些模型可以被重用和重新调整。从第 2 章开始，你将在本书中深入探讨这一点。
当然，你可能也会遇到需要从头开始构建自己的模型的场景。这可以通过 TensorFlow
来完成，但我们在这里只会稍微谈一下，而不是专注于移动场景。本书的姊妹
AI and
Machine Learning for Coders
会重点关注该场景 ...
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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.