嵩阳书院

Python.Machine.Learning.2nd.Edition.2017.9

Python.Machine.Learning.2nd.Edition.2017.9 包含3种格式: 1. Python.Machine.Learning.2nd.Edition.2017.9.pdf 2. Python.Machine.Learning.2nd.Edition.2017.9.epub 3. Python.Machine.Learning.2nd.Edition.2017.9.azw3

ZIP

52.96MB

2021-04-15 22:59

C.Programming.A.Modern.Approach.2nd.Edition

英文版，包括两种：1.文字版。文件小，但是排版有些缺陷2.扫描版。文件大，但是清晰，排版与纸版一样

ZIP

102MB

2019-09-26 03:22

Java核心技术英文版第10版

包括：1.CoreJavaVolumeIFundamentals10thEdition2.CoreJavaVolumeIIAdvancedFeatures10thEdition

ZIP

35.16MB

2019-07-10 15:37

C#高级编程中文第6版_文字版

C#高级编程（中文第6版-文字版）ProfessionalC#2008

PDF

9.37MB

2019-05-13 21:04

CRCDataMiningwithRLearningwithCaseStudies2ndEdition

Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, includi

ZIP

40.27MB

2019-02-27 20:01

SevenConcurrencyModelsinSevenWeeks

包括Seven Concurrency Models in Seven Weeks的中、英文两个版本 Your software needs to leverage multiple cores, handle thousands of users and terabytes of data, and continue working in the face of both hardware and software failure. Concurrency and parallelism are the keys, and Seven Concurrency Models in Seven Weeks equips you for this new world. See how emerging technologies such as actors and functional programming address issues with traditional threads and locks development. Learn how to exploit the parallelism in your computer 's GPU and leverage clusters of machines with MapReduce and Stream Processing. And do it all with the confidence that comes from using tools that help you write crystal clear, high-quality code. This book will show you how to exploit different parallel architectures to improve your code's performance, scalability, and resilience. Learn about the perils of traditional threads and locks programming and how to overcome them through careful design and by working with the standard library. See how actors enable software running on geographically distributed computers to collaborate, handle failure, and create systems that stay up 24/7/365. Understand why shared mutable state is the enemy of robust concurrent code, and see how functional programming together with technologies such as Software Transactional Memory (STM) and automatic parallelism help you tame it. You'll learn about the untapped potential within every GPU and how GPGPU software can unleash it. You'll see how to use MapReduce to harness massive clusters to solve previously intractible problems, and how, in concert with Stream Processing, big data can be tamed. With an understanding of the strengths and weaknesses of each of the different models and hardware architectures, you'll be empowered to tackle any problem with confidence. What You Need: The example code can be compiled and executed on *nix, OS X, or Windows. Instructions on how to download the supporting build systems are given in each chapter. 's GPU and leverage clusters of machines with MapReduce and Stream Processing. And do it all with the confidence that comes from using tools that help you write crystal clear, high-quality code. This book will show you how to exploit different parallel architectures to improve your code's performance, scalability, and resilience. Learn about the perils of traditional threads and locks programming and how to overcome them through careful design and by working with the standard library. See how actors enable software running on geographically distributed computers to collaborate, handle failure, and create systems that stay up 24/7/365. Understand why shared mutable state is the enemy of robust concurrent code, and see how functional programming together with technologies such as Software Transactional Memory (STM) and automatic parallelism help you tame it. You'll learn about the untapped potential within every GPU and how GPGPU software can unleash it. You'll see how to use MapReduce to harness massive clusters to solve previously intractible problems, and how, in concert with Stream Processing, big data can be tamed. With an understanding of the strengths and weaknesses of each of the different models and hardware architectures, you'll be empowered to tackle any problem with confidence. What You Need: The example code can be compiled and executed on *nix, OS X, or Windows. Instructions on how to download the supporting build systems are given in each chapter.

ZIP

13.01MB

2019-02-14 21:24

React16Essentials第二版epubpdf版

React 16 Essentials第二版英文版两种格式： 1. React.16.Essentials.2nd.Edition.2017.11.pdf 2. React.16.Essentials.2nd.Edition.2017.11.epub

ZIP

2.1MB

2019-01-06 14:50

GettingStartedwithVarnishCache2017

Getting Started with Varnish Cache 2017.3英文版两个格式： 1. Getting.Started.with.Varnish.Cache.2017.3.epub 2. Getting.Started.with.Varnish.Cache.2017.3.azw3

zip

6.64MB

2019-01-05 21:52