Database Reliability Engineering Designing and Operating Resilient Database Systems 英文azw3 本资源转载自网络，如有侵权，请联系上传者或csdn删除

PLC应用技术图解项目化教程（西门子S7-300） - 郑长山.azw3，可以在kindele中查看

Python Machine Learning By Example by Yuxi (Hayden) Liu English | 31 May 2017 | ASIN: B01MT7ATL5 | 254 Pages | AZW3 | 3.86 MB Key Features Learn the fundamentals of machine learning and build your own intelligent applications Master the art of building your own machine learning systems with this example-based practical guide Work with important classification and regression algorithms and other machine learning techniques Book Description Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. What you will learn Exploit the power of Python to handle data extraction, manipulation, and exploration techniques Use Python to visualize data spread across multiple dimensions and extract useful features Dive deep into the world of analytics to predict situations correctly Implement machine learning classification and regression algorithms from scratch in Python Be amazed to see the algorithms in action Evaluate the performance of a machine learning model and optimize it Solve interesting real-world problems using machine learning and Python as the journey unfolds About the Author Yuxi (Hayden) Liu is currently a data scientist working on messaging app optimization at a multinational online media corporation in Toronto, Canada. He is focusing on social graph mining, social personalization, user demographics and interests prediction, spam detection, and recommendation systems. He has worked for a few years as a data scientist at several programmatic advertising companies, where he applied his machine learning expertise in ad optimization, click-through rate and conversion rate prediction, and click fraud detection. Yuxi earned his degree from the University of Toronto, and published five IEEE transactions and conference papers during his master's research. He finds it enjoyable to crawl data from websites and derive valuable insights. He is also an investment enthusiast. Table of Contents Getting Started with Python and Machine Learning Exploring the 20 newsgroups data set Spam email detection with Naive Bayes News topic classification with Support Vector Machine Click-through prediction with tree-based algorithms Click-through rate prediction with logistic regression Stock prices prediction with regression algorithms Best practices

Python Machine Learning Cookbook 英文azw3 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

simulink是matlab最重要的组件之一，它提供一个动态系统建模、仿真和综合分析的集成环境。simulink已成为国内外高等院校高等数学、数值分析、数字信号处理、自动控制理论以及工程应用等课程的基本教学工具。 全书共分为17章，从matlab简介开始，详细介绍了simulink的基础知识、模块操作、信号操作、仿真设置、积分器使用、子系统技术、系统仿真过程、模型的调试、编写m语言s-函数及stateflow建模等内容。在本书最后还重点介绍了控制系统仿真系统、神经网络仿真系统、电力系统仿真系统的原理及其运用。 《基于matlab/simulink系统仿真权威指南》按逻辑编排，自始至终用实例描述，是一本简明的simulink综合性参考书。本书深入浅出，实例引导，讲解翔实，既可以作为高等院校理工科的研究生、本科生的教材，也可作为广大科研和工程技术人员的参考用书

高性能MySQL(第3版),包含azw3,epub,mobi格式

创造者 为所有类型的电子书生成Kindle Wordwise（EPUB，MOBI，PRC，AZW3，PDF ...） 您需要在设备上拥有。 usage: php wordwisecreator.php input_file hint_level input_file : path to file need to generate wordwise hint_level : from 1 to 5 default is 5, 1 is less wordwise hint show - only hard word will have definition, 5 is all wordwise hints show

信号完整性揭秘,AZW3格式，方便手机上阅读

kindle高清文字版，可在电脑上用clearview电子书阅读软件阅读。 第1章　从网站重构说起 1.1　糟糕的页面实现，头疼的维护工作 1.2　Web标准——结构、样式和行为的分离 1.3　前端的现状 1.4　打造高品质的前端代码，提高代码的可维护性——精简、重用、有序 第2章　团队合作 2.1　揭秘前端开发工程师 2.2　欲精一行，必先通十行 2.3　增加代码可读性——注释 2.4　提高重用性——公共组件和私有组件的维护 2.5　冗余和精简的矛盾——选择集中还是选择分散 2.6　磨刀不误砍柴工——前期的构思很重要 2.7　制订规范 2.8　团队合作的最大难度不是技术，是人 第3章　高质量的HTML 3.1　标签的语义 3.2　为什么要使用语义化标签 3.3　如何确定你的标签是否语义良好 3.4　常见模块你真的很了解吗 3.4.1　标题和内容 3.4.2　表单 3.4.3　表格 3.4.4　语义化标签应注意的一些其他问题 第4章　高质量的CSS 4.1　怪异模式和DTD 4.2　如何组织CSS 4.3　推荐的base.css 4.4　模块化CSS——在CSS中引入面向对象编程思想 4.4.1　如何划分模块——单一职责 4.4.2　CSS的命名——命名空间的概念 4.4.3　挂多个class还是新建class——多用组合，少用继承 4.4.4　如何处理上下margin 4.5　低权重原则——避免滥用子选择器 4.6　CSS sprite 4.7　CSS的常见问题 4.7.1　CSS的编码风格 4.7.2　id和class 4.7.3　CSS hack 4.7.4　解决超链接访问后hover样式不出现的问题 4.7.5　hasLayout 4.7.6　块级元素和行内元素的区别 4.7.7　display:inline-block和hasLayout 4.7.8　relative、absolute和float 4.7.9　居中 4.7.10　网格布局 4.7.11　z-index的相关问题以及Flash和IE 6下的select元素 4.7.12　插入png图片 4.7.13　多版本IE并存方案——CSS的调试利器IETester 第5章　高质量的JavaScript 5.1　养成良好的编程习惯 5.1.1　团队合作——如何避免JS冲突 5.1.2　给程序一个统一的入口——window.onload和DOMReady 5.1.3　CSS放在页头，JavaScript放在页尾 5.1.4　引入编译的概念——文件压缩 5.2　JavaScript的分层概念和JavaScript库 5.2.1　JavaScript如何分层 5.2.2　base层 5.2.3　common层 5.2.4　page层 5.2.5　JavaScript库 5.3　编程实用技巧 5.3.1　弹性 5.3.2　getElementById、getElementsByTagName和getElements-ByClassName 5.3.3　可复用性 5.3.4　避免产生副作用 5.3.5　通过传参实现定制 5.3.6　控制this关键字的指向 5.3.7　预留回调接口 5.3.8　编程中的DRY规则 5.3.9　用hash对象传参 5.4　面向对象编程 5.4.1　面向过程编程和面向对象编程 5.4.2　JavaScript的面向对象编程 5.4.3　用面向对象方式重写代码 5.5　其他问题 5.5.1　prototype和内置类 5.5.2　标签的自定义属性 5.5.3　标签的内联事件和event对象 5.5.4　利用事件冒泡机制 5.5.5　改变DOM样式的三种方式 附录A　写在规则前面的话 附录B　命名规则 附录C　分工安排 附录D　注释规则 附录E　HTML规范 附录F　CSS规范 附录G　JavaScript规范

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.