Web 2.0 applications provide a rich user experience, but the parts you can't see are just as important-and impressive. They use powerful techniques to process information intelligently and offer features based on patterns and relationships in data. Algorithms of the Intelligent Web shows readers how to use the same techniques employed by household names like Google Ad Sense, Netflix, and Amazon to transform raw data into actionable information.
Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. Readers learn to build Netflix-style recommendation engines, and how to apply the same techniques to social-networking sites. See how click-trace analysis can result in smarter ad rotations. All the examples are designed both to be reused and to illustrate a general technique- an algorithm-that applies to a broad range of scenarios.
As they work through the book's many examples, readers learn about recommendation systems, search and ranking, automatic grouping of similar objects, classification of objects, forecasting models, and autonomous agents. They also become familiar with a large number of open-source libraries and SDKs, and freely available APIs from the hottest sites on the internet, such as Facebook, Google, eBay, and Yahoo.
Dr. Haralambos (Babis) Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions, and also a world expert in supply management. He has about twenty years of experience in developing professional software. Currently, he is the director of R&D and chief architect, for expense management solutions, at Emptoris, Inc. Babis holds a Ph.D. in applied mathematics from Brown University, an M.S. degree in theoretical and applied mechanics from the University of Illinois at Urbana-Champaign, and B.S. and M.S. degrees in civil engineering from the Aristotle University of Thessaloniki in Greece. He was the recipient of the Sigma Xi award for innovative research in 2000, and he is the author of numerous publications in peer-reviewed international scientific journals, conferences, and technical periodicals.
Dmitry Babenko is the lead for the data warehouse infrastructure at Emptoris, Inc. He is a software engineer and architect with 13 years of experience in the IT industry. He has designed and built a wide variety of applications and infrastructure frameworks for banking, insurance, supply-chain management, and business intelligence companies. He received a M.S. degree in computer science from Belarussian State University of Informatics and Radioelectronics.
花了半个多月的时间断断续续地看完了这本书,说说感受。 1. 先说这本书的适用人群,在译者序里说是学生和需要梳理的工作者,但是在我看来,我觉得最佳的订位,应该是之前没有过相关经验,然后需要用最快的速度完成一个智能系统的人。因为本书把所有的知识简单化,当然随之的也...
评分花了半个多月的时间断断续续地看完了这本书,说说感受。 1. 先说这本书的适用人群,在译者序里说是学生和需要梳理的工作者,但是在我看来,我觉得最佳的订位,应该是之前没有过相关经验,然后需要用最快的速度完成一个智能系统的人。因为本书把所有的知识简单化,当然随之的也...
评分花了半个多月的时间断断续续地看完了这本书,说说感受。 1. 先说这本书的适用人群,在译者序里说是学生和需要梳理的工作者,但是在我看来,我觉得最佳的订位,应该是之前没有过相关经验,然后需要用最快的速度完成一个智能系统的人。因为本书把所有的知识简单化,当然随之的也...
评分可以作为智能算法学习的起点,覆盖了搜索、推荐、聚类、分类等领域,有大量实用的示例代码,提供了很多扩展阅读的资源,以此为线索可以帮助我们循序渐进的深入智能算法的领域。 不足之处: 书中代码的部分常常没有事先说明思路,直接先上代码,而代码中琐碎无关的部分,以及排...
评分可以作为智能算法学习的起点,覆盖了搜索、推荐、聚类、分类等领域,有大量实用的示例代码,提供了很多扩展阅读的资源,以此为线索可以帮助我们循序渐进的深入智能算法的领域。 不足之处: 书中代码的部分常常没有事先说明思路,直接先上代码,而代码中琐碎无关的部分,以及排...
很不错,但是距离好的实现还是有一大段距离,摸索中前进吧。
评分这种书里使劲贴什么代码...注意品味...
评分简略介绍了一些常用的算法和技术,需要一些数学背景知识,讲的不详细
评分很不错的科普,但是不够系统全面,只有一些例子
评分Great book in to Intelligence.
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