作者:
[美] 佩德罗·多明戈斯 译者:
黄芳萍 出版社:中信出版社 出版年: 2017-1-1 ISBN: 9787508668673 页数: 402 装帧: 平装 定价: 68.00元 原作名: The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Privacy is only one aspect of the larger issue of data sharing, and if we focus on it to the detriment of the whole, as much of the dabate to date has, we risk reaching the wrong conclusions. ... When people have to trade off privacy against other benefits, as when filling out a profile on a website, the implied value of privacy that comes out is much lower than if you ask them abstract questions like “Do you care about your privacy?” But privacy debates are more often framed in terms of the latter. … Privacy is not a zero-sum game, even though it’s often treated like one. ––To share or not to share, and how and where (查看原文)
In the early days of AI, the common view was that computers would replace blue-collar workers before white-collar ones, because white-collar work requires more brains. But that’s not quite how things turned out. Robots assemble cars, but they haven’t replaced construction workers. On the other hand, machine-learning algorithms have replaced credit analysts and direct marketers. … The common theme is that narrowly defined tasks are easily learned from data, but tasks that require a broad combination of skills and knowledge aren’t. Most of your brain is devoted to vision and motion, which is a sign that walking around is much more complex than it seems; we just take it for granted because, having been honed to perfection by evolution, it’s mostly done subconsciously. ––A neural network stole... (查看原文)
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Basic Books2015版（其他版本）
西溪近园
41 有用 Ecthelion 2017-08-23 06:18:23
又是中信……一再用这么可怕的翻译糟蹋科普，这是存心误人子弟吧，望天。
3 有用 ddcrystal 2019-12-03 09:11:24
本书分析了各个机器学习学派的算法，整理如下: 符号学派:逆向演绎，决策树 联结学派:神经网络，感知机，反向传播，稀疏自动编码器 进化学派:遗传算法 贝叶斯学派:朴素贝叶斯分类器，马尔科夫链，隐藏马尔科夫模型，贝叶斯网络，环路信念传播，马尔科夫链蒙特卡洛理论，马尔科夫网络 类推学派:最近邻算法，支持向量机，类比推理法 无监督学习:聚类问题，K均值算法，期望最大化算法(EM)，PCA(主要成分分析)，... 本书分析了各个机器学习学派的算法，整理如下: 符号学派:逆向演绎，决策树 联结学派:神经网络，感知机，反向传播，稀疏自动编码器 进化学派:遗传算法 贝叶斯学派:朴素贝叶斯分类器，马尔科夫链，隐藏马尔科夫模型，贝叶斯网络，环路信念传播，马尔科夫链蒙特卡洛理论，马尔科夫网络 类推学派:最近邻算法，支持向量机，类比推理法 无监督学习:聚类问题，K均值算法，期望最大化算法(EM)，PCA(主要成分分析)，非线性降维算法，等距映射算法，强化学习，元算法，关联学习 但是算法原理，我看的似懂非懂。本书算是个概述，后续想学习哪一部分可以参考后面的延伸阅读。 (展开)
1 有用 玄之 2018-03-12 03:23:58
翻譯的略晦澀。類似技術問題不如看公式來得直接。
2 有用 和光 2018-02-15 10:19:21
从头到尾没整明白，不妨碍我读得很嗨。不知道是我逻辑性差、知识库小还是翻译确实辣鸡。人类的进步史就是工具外化进步的过程，直到造出另一个人。整本书在讨论向人和自然学习“如何学习”，从而写出自动写程序的程序。贝叶斯算法那部分让我想起张仲景《伤寒杂病论》里的条文。逻辑和概率。基因、细胞和脑神经认知。算法。
14 有用 邻家の小宇宙 2017-12-04 18:27:33
“你的工作会在多大程度上利用到你的大脑？用的越多，你就越安全。”“不要试图与机器人竞争，而是要利用它”