HFSS软件学习的良好教材,此文档完整清晰。方便学生自学!
2019-12-21 19:31:36 11.71MB HFSS 李明洋
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Book Description Written for the moderately experienced Java programmer, this book builds on readers¿ existing knowledge of object-oriented programming and covers all important aspects of Standard C++—emphasizing more lower-level C-style details later in the presentation. Chapter topics include philosophy of C++, simplest C++, pointers and reference variables, object-based programming: classes, operator overloading, object-oriented programming: inheritance, templates, abnormal control flow, input and output, collections: the standard template library, primitive arrays and strings, C-style C++, and using Java and C++: the JNI. For new C++ programmers converted from Java. For experienced Java programmers and students who require the skills of C++ programming, best-selling author Mark Allen Weiss bridges the gap. He efficiently presents the complex C++ language in this well-designed tutorial/reference that both students and seasoned programmers will appreciate. The book is ideal as a primary text for intermediate C++ courses, as a supplemental no-nonsense reference for other courses, or for independent learning by professionals. C++ for Java Programmers is a concise, well-written text that provides authoritative and up-to-date coverage of key features and details of C++, with a special focus on how C++ compares to Java. The book's approach shows knowledgeable students or professionals how to grasp the complexities of C++ and harness its power by mutually addressing the benefits and the pitfalls of the two languages. By highlighting the features and comparative elements of each language, and building on the reader's existing knowledge of object-oriented programming, C++ for Java Programmers enables users to master the essentials of C++ quickly and thoroughly. Key Features Includes insightful comparisons of the two programming languages throughout the text and points out the subtleties of C++ Succinctly covers the pertinent highlights of STL (Standard Template Library
2019-12-21 19:29:21 8.94MB C++ Java
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本资源为UART标准协议规范,对于UART开发及应用具有很大帮助。
2019-12-21 19:28:44 160KB UART 协议 规范 spec
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史上最好的STLSTL源码剖析阅读版本,超级高清,超用心的添加了阅读目录,方便了你的阅读,不再难受的看那些简陋的模糊的,扫描版。下载过的筒子们,把这本书顶起来吧,绝对的完爆之前所有无耻版本。
2019-12-21 19:28:42 17.78MB STL源码
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离散时间信号处理奥本海姆第2版 奥本海姆编的离散时间信号处理应该是信号处理这一块最好的书了
2019-12-21 19:23:20 18.23MB 奥本海姆 DSP
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【现在对做电子书还蛮有经验和一套了,书签制作,PDF获取都还可以了,有一套经验了,以后有空弄成自动化的了!不过也只能共享一部分给大家,不要太过分了!】是不是已经厌倦了那些深奥的HTML书?你可能在抱怨,只有成为专家之后才能读懂那些书。那么,找一本新修订的《Head First HTML与CSS(第2版)》吧,来真正学习HTML。你可能希望学会HTML和CSS来创建你想要的Web页面,从而能与朋友、家人、粉丝和狂热的顾客更有效地交流。你还希望使用最新的HTML5标准,能够保证随时间维护和扩展你的Web页面,使它们在所有浏览器和移动设备中都能正常工作。
2019-12-21 18:58:13 175.66MB Head First HTML与CSS 第2版
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《Python学习笔记》。是一个名为:雨痕的前辈写的。虽然是未完成版,但是读起来很顺畅,于是周末两天,除了逛街就是在读这本书。不到200页的电子书,很快可以读完。 书分为三个部分:Python语言,Python标准库,Python扩展库。第一部分作者是已经完成了,从Python的运行原理,到每种数据类型的在内存中的状态,对应的C的实现。
2019-12-21 18:57:26 1.45MB Python笔记 雨痕 Python编程 深入python
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适合新手入门机器学习和tensorflow的最佳教程,强烈推荐。 Chapter 1: Getting Started with TensorFlow Chapter 2: The TensorFlow Way Chapter 3: Linear Regression Chapter 4: Support Vector Machines Chapter 5: Nearest Neighbor Methods Chapter 6: Neural Networks Chapter 7: Natural Language Processing Chapter 8: Convolutional Neural Networks Chapter 9: Recurrent Neural Networks Chapter 10: Taking TensorFlow to Production Chapter 11: More with TensorFlow
2019-12-21 18:56:29 4.55MB 深度学习 deep learning tensorflow
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本微软面试100题系列,共计11篇文章,300多道面试题,截取本blog索引性文章:程序员面试、算法研究、编程艺术、红黑树、数据挖掘5大系列集锦:http://blog.csdn.net/v_july_v/article/details/6543438,中的第一部分编辑而成,涵盖了数据结构、算法、海量数据处理等3大主题。 闲不多说,眼下九月正是校招,各种笔试,面试进行火热的时节,希望此份微软面试100题系列的PDF文档能给正在找工作的朋友助一臂之力! 如果读者发现了本系列任何一题的答案有问题,错误,bug,恳请随时不吝指正,你可以直接评论在原文之下,也可以通过私信联系我。 祝诸君均能找到令自己满意的offer或工作,谢谢。July、二零一二年九月二十日
2019-12-21 18:56:22 4.43MB 微软面试 100题
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TensorFlow Machine Learning Cookbook by Nick McClureEnglish | 14 Feb. 2017 | ISBN: 1786462168 | 370 Pages Key FeaturesYour quick guide to implementing TensorFlow in your day-to-day machine learning activitiesLearn advanced techniques that bring more accuracy and speed to machine learningUpgrade your knowledge to the second generation of machine learning with this guide on TensorFlowBook DescriptionTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google's machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.What you will learnBecome familiar with the basics of the TensorFlow machine learning libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks and improve predictionsApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesTake TensorFlow into productionAbout the AuthorNick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow and Caesar's Entertainment. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict an
2019-12-21 18:55:57 4.55MB TensorFlow Machine Learning Python
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