C语言课程设计的优点主要体现在以下几个方面： 基础性强：C语言是一门基础性的编程语言，它直接涉及到计算机的内存管理、指针操作等底层知识。学习C语言有助于深入理解计算机的工作原理，为后续学习其他高级语言打下坚实基础。 可移植性好：C语言编写的程序可以在多种操作系统和硬件平台上运行，因此，学习C语言可以帮助学生掌握跨平台编程的技能，提高程序的可移植性。 效率高：C语言具有高效性，它可以直接访问硬件资源，执行效率高。在编写系统级软件、嵌入式系统、游戏开发等领域，C语言具有明显优势。 结构清晰：C语言采用结构化编程思想，有助于培养学生的逻辑思维能力和程序设计能力。通过C语言的学习，学生可以掌握如何合理组织代码、设计算法和数据结构。 资源丰富：C语言拥有丰富的学习资源和社区支持，包括教材、在线课程、论坛等。学生可以通过这些资源自主学习，解决遇到的问题，提高编程能力。 实践性强：C语言课程设计通常包含大量的实践环节，如编写小程序、实现算法等。这些实践环节有助于提高学生的动手能力和解决问题的能力，使他们更好地将理论知识应用于实际项目中。 综上所述，C语言课程设计具有基础性强、可移植性好、效率高、结构清晰、资源丰富和实践性强等优点。通过C语言的学习，学生可以掌握编程的基本技能，为后续的专业学习和职业发展奠定坚实基础。

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Title: Hadoop in Practice, 2nd Edition Author: Alex Holmes Length: 512 pages Edition: 2 Language: English Publisher: Manning Publications Publication Date: 2014-10-12 ISBN-10: 1617292222 ISBN-13: 9781617292224 Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents Part 1: Background and fundamentals Chapter 1: Hadoop in a heartbeat Chapter 2: Introduction to YARN Part 2: Data logistics Chapter 3: Data serialization— working with text and beyond Chapter 4: Organizing and optimizing data in HDFS Chapter 5: Moving data into and out of Hadoop Part 3: Big data patterns Chapter 6: Applying MapReduce patterns to big data Chapter 7: Utilizing data structures and algorithms at scale Chapter 8: Tuning, debugging, and testing Part 4: Beyond MapReduce Chapter 9: SQL on Hadoop Chapter 10: Writing a YARN application Appendix: Installing Hadoop and friends

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Java第二版中的自然语言处理 这是Packt发行的《 进行的代码库。 用于NLP的机器学习和神经网络模型的构建技术 这本书是关于什么的？ 自然语言处理（NLP）允许您使用任何句子并识别模式，特殊名称，公司名称等。 《 Java自然语言处理》第二版教您如何在Java库的帮助下执行语言分析，同时不断从结果中获得见解。 本书涵盖以下激动人心的功能： 了解基本的NLP任务以及它们之间的关系 发现并使用可用的令牌化引擎 应用搜索技术来查找文档中的人物和事物 构建解决方案以识别句子中的词性 使用解析器提取文档元素之间的关系 如果您觉得这本书适合您，请立即获取！ 说明和导航 所有代码都组织在文件夹中。 例如，Chapter02。 该代码将如下所示： System.out.println(tagger.tagString("AFAIK she H8 cth!")); System.out

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