machine-learning-algorithms 机器学习算法

This book is an introduction to the world of machine learning, a topic that is becoming more and more important, not only for IT professionals and analysts but also for all those scientists and engineers who want to exploit the enormous power of techniques such as predictive analysis, classification,clustering and natural language processing. Of course, it's impossible to cover all the details with the appropriate precision; for this reason, some topics are only briefly described, giving the user the double opportunity to focus only on some fundamental concepts and, through the references, examine in depth all those elements that will generate much interest. I apologize in advance for any imprecision or mistakes, and I'd like to thank all Packt editors for their collaboration and constant attention.

Machine Learning with Spark - 2nd Edition

Throughout this book, we will focus on real-world applications of machine learning technology. While we may briefly delve into some theoretical aspects of machine learning algorithms and required maths for machine learning, the book will generally take a practical, applied approach with a focus on using examples and code to illustrate how to effectively use the features of Spark and MLlib, as well as other well-known and freely available packages for machine learning and data analysis, to create a useful machine learning system.

Hands-On Machine Learning with Scikit-Learn and TensorFlow ...

This book assumes that you know close to nothing about Machine Learning. Its goal is to give you the concepts, the intuitions, and the tools you need to actually implement programs capable of learning from data. We will cover a large number of techniques, from the simplest and most commonly used (such as linear regression) to some of the Deep Learning techniques that regularly win competitions. Rather than implementing our own toy versions of each algorithm, we will be using actual production-ready Python frameworks: Scikit-Learn is very easy to use, yet it implements many Machine Learning algorithms efficiently, so it makes for a great entry point to learn Machine Learning. TensorFlow is a more complex library for distributed numerical computation using data flow graphs. It makes it possible to train and run very large neural networks efficiently by distributing the computations across potentially thousands of multi-GPU servers. TensorFlow was created at Google and supports many of their large- scale Machine Learning applications.

用户网络行为画像:大数据中的用户网络行为画像

如何能牢牢地黏住老用户、吸引新用户、读懂用户的偏好兴趣和喜怒哀乐，这都是对企业发展至关重要甚至关乎生死存亡的问题，解决这个问题的方法就是推荐系统。本书分为上中下三篇，共13章，上篇为用户画像知识工程基础，包括表征建模、画像计算、存储及各种更新维护等管理操作；中篇为推荐系统与用户画像，包括传统协同过滤等经典推荐算法的介绍，以及涉及用户画像的推荐方法；下篇为应用案例分析，包括Netflix、阿里等数据竞赛的经典数据案例，以及在具体工程开发过程的具体案例，分别从系统需求、总体结构、算法设计、运行流程及测试结果等五个方面提供详细案例指导。

Beginning Spring Boot 2 Applications and Microservices with the Spring Framework

Copyright © 2017 by K. Siva Prasad Reddy Spring is the most popular Java-based framework for building enterprise applications. The Spring framework provides a rich ecosystem of projects to address modern application needs, like security, simplified access to relational and NoSQL datastores, batch processing, integration with social networking sites, large volume of data streams processing, etc. As Spring is a very flexible and customizable framework, there are usually multiple ways to configure the application. Although it is a good thing to have multiple options, it can be overwhelming to the beginners. Spring Boot addresses this “Spring applications need complex configuration” problem by using its powerful autoconfiguration mechanism. Spring Boot is an opinionated framework following the “Convention Over Configuration” approach, which helps build Spring-based applications quickly and easily. The main goal of Spring Boot is to quickly create Spring-based applications without requiring the developers to write the same boilerplate configuration again and again. In recent years, the microservices architecture has become the preferred architecture style for building complex enterprise applications. Spring Boot is a great choice for building microservices-based applications using various Spring Cloud modules. This book will help you understand what Spring Boot is, how Spring Boot helps you build Spring-based applications quickly and easily, and the inner workings of Spring Boot using easy-to-follow examples.

Hadoop MapReduce 实战手册

这是一本学习Hadoop MapReduce 的一站式指南，完整介绍了 Hadoop生态体系，包括Hadoop平台安装、部署、运维等，以及 Hadoop生态系统成员Hive、Pig、HBase、Mahout等。最重要的是，书 中包含丰富的示例和多样的实际应用场景，以一种简单而直接的方式 呈现了90个实战攻略，并给出一步步的指导。本书从获取Hadoop并 在集群中运行Hadoop讲起，依次介绍了高级HDFS，高级Hadoop MapReduce管理，开发复杂的Hadoop MapReduce应用程序，Hadoop的 生态系统，统计分析，搜索与索引，聚类、推荐和寻找关联，海量文 本数据处理，云部署等内容。

Learning PySpark.pdf

In this book, we will guide you through the latest incarnation of Apache Spark using Python. We will show you how to read structured and unstructured data, how to use some fundamental data types available in PySpark, build machine learning models, operate on graphs, read streaming data, and deploy your models in the cloud. Each chapter will tackle different problem, and by the end of the book we hope you will be knowledgeable enough to solve other problems we did not have space to cover here.

Deep Learning with Hadoop.pdf

Deep Learning with Hadoop Copyright © 2017 Packt Publishing 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. First published: February 2017 Production reference: 1130217 Published by Packt Publishing Ltd.

Hadoop 2.x Administration Cookbook

Hadoop is a distributed system with a large ecosystem, which is growing at an exponential rate, and hence it becomes important to get a grip on things and do a deep dive into the functioning of a Hadoop cluster in production. Whether you are new to Hadoop or a seasoned Hadoop specialist, this recipe book contains recipes to deep dive into Hadoop cluster configuration and optimization.

Docker开发指南 pdf

第一部分首先讲解什么是容器，以及为什么应该关注它。之后将示范Docker的基本操作。 最后会用较长篇幅来讲解 Docker 的基本概念和技术，其中包括 Docker 命令的概览。 ?? 第二部分讲解如何将 Docker 应用于软件开发的生命周期。首先讲解如何配置开发环境， 然后构建一个简单的 Web 应用，这个 Web 应用的例子将用于整个第二部分。这一部分还会涵盖开发、测试、集成，以及如何部署容器，如何有效地监控和记录生产环境的日志。 ?? 第三部分的内容更为深入，其中包括在多主机集群环境中，有哪些工具及技巧能使Docker 容器既安全又可靠地运行。这部分适合已经使用 Docker，并需要了解如何扩展或解决网络和安全问题的读者。