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英國出版界指標大獎肯定!A.F. Steadman 獲年度作家,《史坎德》系列帶你踏上熱血奇幻旅程
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Modern Embedded Computing

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出版日:2011/05/19 作者:Michael Metcalf; John Reid; Malcolm Cohen  出版社:OUP Academic UK  裝訂:平裝
Fortran remains one of the principal programming languages used in high-performance scientific, numerical, and engineering computing. A series of significant revisions to the standard versions of the
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出版日:2011/02/18 作者:Mark Shepard  出版社:Mit Pr  裝訂:平裝
Our cities are “smart” and getting smarter as information processing capability is embedded throughout more and more of our urban infrastructure. Few of us object to traffic light control
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出版日:2018/09/18 作者:Inc. Dorling Kindersley (COR); Lucy Rogers (FRW)  出版社:DK Pub  裝訂:精裝
Explore fascinating robotic technology through the ages, from the earliest automatons to modern humanoid helpers.From automata created by Leonardo Da Vinci to modern-day androids and animal robots, this book covers artificial intelligence (AI) throughout history. Discover the latest at the cutting edge of robotics, where science, technology, mechanical engineering, and computing meet as The Robot Book explains how robots work, how they are made, and how they help and sometimes hinder in modern society.This kids' robot book showcases the latest and greatest innovations in AI through bright graphics and stunning photography. Tech panels present fascinating facts about each robot's design, production, and capability. A thematic approach covers a range of subjects, including the most iconic robots in popular culture and robots in the workforce. The final chapter covers the future of robotics, and the opportunities and pitfalls of using robots more and more in our everyday life.Young reader
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出版日:2017/09/25 作者:Wes Mckinney  出版社:OREILLY MEDIA  裝訂:平裝
Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? The second edition of this hands-on guide—updated for Python 3.5 and Pandas 1.0—is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems, using Python libraries such as NumPy, pandas, matplotlib, and IPython.Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.
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