构建云上的数据湖-AWS

Spark学习笔记 Spark学习笔记 Spark学习笔记

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies. . Read more... Abstract: This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

数据中心大数据的冗余避免：传统的神经网络方法

基于决策树的鸢(yuan)尾花分类考察基于四个特征联合描述样本，构造的二叉分类决策树模型，决策树的可视化。 步骤：1. (1)导入scikit-learn内置的datasets 数据集模块 (2)导入scikit-learn内置的tree包的 DecisionTreeClassifier API接口模块 2-2. 决策树的可视化 3. 有关参数设置： Parameters 类别数=3； 绘制颜色表； 步长 4. 加载iris数据集,获取该数据集对象的data部分，以及类别标号 5. 初始化决策树分类模型实例；并基于X，y 训练集，学习CART分类树 并且详细介绍了参数的应用

【资料合集】UG220723-北京-大数据Meetup

给大家分享一套大数据课程，共27周，提供代码、数据等配套资料下载。

数据中心 云 大数据 网络技术 红宝书

cdh5.12安装文档，亲测可用，根据文档步骤可以安装cdh5.x系列。

交易系统数据模型-实体关系 最简单的交易模型