Introduction to Middleware Web Services, Object Components, and Cloud Computing 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除 本资源转载自网络,如有侵权,请联系上传者或csdn删除
2022-07-06 16:05:33 21.05MB Introduction Middleware Web Services
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Homological Algebra has grown in the nearly three decades since the first edition of this book appeared in 1979. Two books discussing more recent results are Weibel, An Introduction to Homological Algebra, 1994, and Gelfand– Manin, Methods of Homological Algebra, 2003. In their Foreword, Gelfand and Manin divide the history of Homological Algebra into three periods: the first period ended in the early 1960s, culminating in applications of Homological Algebra to regular local rings. The second period, greatly influenced by the work of A. Grothendieck and J.-P. Serre, continued through the 1980s; it involves abelian categories and sheaf cohomology. The third period, involving derived categories and triangulated categories, is still ongoing. Both of these newer books discuss all three periods (see also Kashiwara–Schapira, Categories and Sheaves). The original version of this book discussed the first period only; this new edition remains at the same introductory level, but it now introduces the second period as well. This change makes sense pedagogically, for there has been a change in the mathematics population since 1979; today, virtually all mathematics graduate students have learned something about functors and categories, and so I can now take the categorical viewpoint more seriously.
2022-07-04 19:27:24 3.28MB maths algebra number
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Introduction about VxWorks 7 technology
2022-07-04 19:01:01 2.32MB vxworks
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光滑流形的经典教材,热爱数学或者研究机器视觉,计算机视觉的朋友可以参考
2022-06-30 21:53:04 7.39MB 流形
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Linux程序设计教学课件:Ch0 Course Introduction.pdf
2022-06-30 18:01:02 102KB Linux程序设计
TCPIP协议原理教学课件:Chapter 1 Introduction.ppt
2022-06-28 09:06:22 566KB TCPIP
Python是访问、操作和从各种数据中获得见解的理想选择。Python for Data Science通过根植于实际示例和实践活动的边做边学的方法向您介绍Python的数据分析世界。您将学习如何编写Python代码来获取、转换和分析数据,为业务管理、市场营销和决策支持中的用例实践最先进的数据处理技术。 您将发现Python丰富的用于基本操作的内置数据结构集,以及用于数据科学的健壮的开源库生态系统,包括NumPy、pandas、scikit-learn、matplotlib等。这些示例展示了如何以各种格式加载数据,如何简化、分组和聚合数据集,以及如何创建图表、地图和其他可视化功能。后面的章节将深入展示真实世界的数据应用,包括使用位置数据为出租车服务提供动力,市场篮子分析来识别共同购买的商品,以及机器学习来预测股票价格。 这本书从数据处理和分析的概念介绍开始,解释一个典型的数据处理管道。然后,我们将介绍Python的内置数据结构和一些广泛用于数据科学应用程序的第三方Python库。接下来,我们将探讨用于获取、组合、聚合、分组、分析和可视化不同大小和数据类型的数据集的日益复杂的技术。随
2022-06-25 20:05:30 2.35MB python
计算模型与算法技术:1-Introduction.ppt
2022-06-24 09:08:35 1.09MB 计算模型与算法技术
操作系统英文课件:ch1 Introduction.ppt
2022-06-24 09:00:55 2.79MB 操作系统
数字逻辑设计第1章 Introduction (引言).ppt
2022-06-23 09:08:50 2.24MB 数字逻辑设计