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出版日:2018/01/09 作者:Edited by Tracy Lee  出版社:CRC Press UK  裝訂:精裝
The proceedings of DOSFIAC 2017 consist of papers on topics such as artificial intelligence, machine learning, big data, cloud computing, IOT, smart reservoir, visualization, GIS and SCADA systems. Th
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出版日:2017/12/18 作者:Momiao Xiong; Joshua Akey  出版社:Chapman & Hall  裝訂:精裝
Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is u
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出版日:2017/11/23 作者:Jacek Grekow  出版社:Springer-Verlag New York Inc  裝訂:精裝
The problems it addresses include emotion representation, annotation of music excerpts, feature extraction, and machine learning. The book chiefly focuses on content-based analysis of music files, a s
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出版日:2017/09/29 作者:日經大數據  出版社:財經傳訊  裝訂:平裝
你要聽特斯拉馬斯克的或是臉書祖克伯的?前者認為人工智慧(AI)會毁滅人類,後者說不會!其實你應聽Google的,它提供平台讓中小企業也可以搭上人工智慧的特快車! 將衝擊世界的人工智慧類型基本上是指會自己學習的電腦,也就是所謂的機器學習(Machine Learning)及深度學習(Deep learning),而非過去大家習慣的電腦依程式行事。前者是指機器自己由大量資料中,得出某結論,如給電腦一堆
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出版日:2017/07/11 作者:何宇健  出版社:電子工業出版社  裝訂:平裝
Python與機器學習這一話題是如此的寬廣,僅靠一本書自然不可能涵蓋到方方面面,甚至即使出一個系列也難能做到這點。單就機器學習而言,其領域就包括但不限於如下:有監督學習(Supervised Learning),無監督學習(Unsupervised Learning)和半監督學習(Semi-Supervised Learning)。而具體的問題又大致可以分兩類:分類問題(Classificatio
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Business in Real-time Using Azure Iot and Cortana Intelligence Suite ― Driving Your Digital Transformation
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出版日:2017/06/07 作者:Bob Familiar; Jeff Barnes  出版社:Apress  裝訂:平裝
Learn how today’s businesses can transform themselves by leveraging real-time data and advanced machine learning analytics. This book provides prescriptive guidance for architects and develo
定價:2899 元
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出版日:2016/12/23 作者:Tamir Hazan; George Papandreou; Daniel Tarlow  出版社:Mit Pr  裝訂:精裝
In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a s
出版日:2016/08/05 作者:佩德羅.多明戈斯-作; 謝孫源 審訂  出版社:三采文化  裝訂:精裝
★CNN、《新科學人》、《經濟學人》、《柯克斯書評》等多家媒體推薦報導★比爾.蓋茲年度選書!揭開大數據、人工智慧、機器學習的祕密,打造人類文明史上最強大的科技——終極演算法!有一個終極演算法,可以解開宇宙所有的祕密,現在大家都在競爭,誰能最先解開它!.機器學習是什麼?大演算又是什麼?.大演算如何運作與發展,機器可以預測什麼?.我們可以信任機器學過的東西嗎?.商業、政治為什麼要擁抱機器學習?.不只商
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出版日:2015/05/07 作者:Drew Conway; John Myles White  出版社:碁峰資訊  裝訂:平裝
內容簡介:「本書提供許多絕佳的機器學習實用案例。有別於工具書或理論證明,本書著重於實際問題處理,因此具備程式設計背景及對機器學習有興趣的讀者們均可輕鬆入門。」 - Max Shron, OkCupid 如果你是平時喜歡上網蒐集各種資料的程式設計師,想尋找並學習資料分析的方法與工具,本書將會是您了解機器學習最好的起點。在Machine Learning領域中,包含各種分析問題的工具與方法,可以讓我們
出版日:2014/12/05 作者:Sebastian Nowozin; Peter V. Gehler; Jeremy Jancsary; Christoph H. Lampert  出版社:Mit Pr  裝訂:精裝
The goal of structured prediction is to build machine learning models that predictrelational information that itself has structure, such as being composed of multiple interrelatedparts. These models,
Industrial Strength Empirical Modeling
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出版日:2014/08/08 作者:Guido Smits; Mark Kotanchek; Arthur Kordon; Alex Kalos  出版社:IEEE  裝訂:精裝
Industrial Strength Empirical Modeling clearly explains the main principles of the different machine learning approaches and offers a methodology of how to integrate these techniques for successful r
優惠價: 9 2734
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出版日:2014/02/28 作者:Hendrik Blockeel; Saao D~eroski; Jan Struyf; Bernard enko  出版社:Springer-Verlag New York Inc  裝訂:精裝
This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techn
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出版日:2014/02/19 作者:Peter J. Hoffman; Eric S. Hopewell; Brian Janes  出版社:Cengage Learning  裝訂:精裝
Packed with detailed examples and illustrations, PRECISION MACHINING TECHNOLOGY, 2e delivers the ideal introduction to today's machine tool industry, equipping readers with a solid understanding of fu
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出版日:2012/06/06 作者:David D. Busch  出版社:Cengage Learning  裝訂:平裝
The Sony NEX-7 is one of the most innovative cameras Sony has ever introduced. It is the flagship of Sony's NEX product line, a whole new type of picture-taking machine, combining a tiny, mirrorless b
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出版日:2012/05/18 作者:Robert E. Schapire; Yoav Freund  出版社:Mit Pr  裝訂:精裝
Boosting is an approach to machine learning based on the idea of creating a highlyaccurate predictor by combining many weak and inaccurate "rules of thumb." A remarkablyrich theory has evolved around
出版日:2011/03/01 作者:Neal Bascomb  出版社:Crown Publishers  裝訂:精裝
That Monday afternoon, in high-school gyms across America, kids were battling for the only glory American culture seems to want to dispense to the young these days: sports glory.? But at Dos Pueblos High School in Goleta, California, in a gear-cluttered classroom, a different type of “cool” was brewing.? A physics teacher with a dream – the first public high-school teacher ever to win a MacArthur Genius Award -- had rounded up a band of high-I.Q. students who wanted to put their technical know-how to work.? If you asked these brainiacs what the stakes were that first week of their project, they’d have told you it was all about winning a robotics competition – building the ultimate robot and prevailing in a machine-to-machine contest in front of 25,000 screaming fans at Atlanta’s Georgia Dome.?But for their mentor, Amir Abo-Shaeer, much more hung in the balance. ?The fact was, Amir had in mind a different vision for education, one based not on rote learning -- on absorbing facts and fig
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出版日:2008/04/01 作者:黃開竹  出版社:浙江大學出版社  裝訂:平裝
Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms。 Specifically, the book distinguishes the inner nature
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出版日:2007/07/27 作者:Gokhan Bakir; Thomas Hofmann; Alexander J. Smola; Ben Taskar; S. V. N. Vishwanathan  出版社:Mit Pr  裝訂:精裝
Machine learning develops intelligent computer systems that are able to generalizefrom previously seen examples. A new domain of machine learning, in which the prediction mustsatisfy the additional co
出版日:2007/07/27 作者:Gokhan Bakir  出版社:Mit Pr  裝訂:平裝
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure. Machine learning develops intelligent computer systems that are able to genera
出版日:2007/03/23 作者:Peter D. Grnnwald; Jorma Rissanen  出版社:Mit Pr  裝訂:精裝
The minimum description length (MDL) principle is a powerful method of inductive inference, the basis of statistical modeling, pattern recognition, and machine learning. It holds that the best explan
出版日:2006/05/01 作者:Alan Beaulieu  出版社:美商歐萊禮  裝訂:平裝
SQL,是關聯式資料庫的通用語。它是種不太獨立、與其他程式語言(如 C++、Java、Python與Perl)息息相關的語言。關聯式資料庫現在已普遍存在,使用者們至少該有些關於這種語言的知識。重要內容包括: *一口氣向很多個資料表收集與回傳關聯性資訊。這稱為聯結(join),是SQL 的運作核心。 *採用集合導向的資料操作方式。SQL 幾乎都是集合的操作,如果不好好利用這項優勢,就等於錯失SQ
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出版日:2005/02/25 作者:PeterD. Grunwald  出版社:Bradford Books  裝訂:精裝
The process of inductive inference -- to infer general laws and principles from particular instances -- is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Des
出版日:2004/11/19 作者:Hillol Kargupta; Anupam Joshi; Krishnamoorthy Sivakumar; Yelena Yesha  出版社:PBKAAAIP  裝訂:平裝
Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recog
出版日:2000/04/24 作者:YaserS. Abu-Mostafa  出版社:Mit Pr  裝訂:平裝
This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an excit
出版日:1995/12/28 作者:Francesco Bergadano  出版社:Mit Pr  裝訂:精裝
Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the re
Nonlinear Programming
90 折
出版日:1995/01/01 作者:Olvi L. Mangasarian  出版社:Cambridge University Press  裝訂:平裝
A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, s
優惠價: 9 2754
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出版日:2018/10/15 作者:William Gunnells  出版社:Jones & Bartlett Learning  裝訂:精裝
Most books on programming focus on the skill level of the reader rather then the topic. This book is ideal for both the experienced programmer, or the absolute beginner looking for an introduction to
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