Wydawca: Packt Publishing

Learning Predictive Analytics with R. Get to grips with key data visualization and predictive analytic skills using R

Eric Mayor

This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data.You will learn how to perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further.The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Naïve Bayes, decision trees, and text mining. It also provides a description of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages.

Learning PrimeFaces Extensions Development. This book covers all the knowledge you need to start developing extended or advanced PrimeFaces applications. With lots of screenshots and a clear step-by-step approach, it makes learning an enjoyable process

Sudheer Jonna

This book provides a step by step approach that explains the most important extension components and their features. All the major features are explained by using the JobHub application with supporting screenshots. If you are an intermediate to advanced level user (or developer) who already has a basic working knowledge of PrimeFaces, then this book is for you. The only thing you need to know is Java Server Faces(JSF).

Learning Probabilistic Graphical Models in R. Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R

David Bellot

Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models.We’ll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we’ll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you’ll see the advantage of going probabilistic when you want to do prediction. Next, you’ll master using R packages and implementing its techniques. Finally, you’ll be presented with machine learning applications that have a direct impact in many fields. Here, we’ll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems.

Learning Proxmox VE. Unleash the power of Proxmox VE by setting up a dedicated virtual environment to serve both containers and virtual machines

Rik Goldman

Proxmox VE 4.1 provides an open source, enterprise virtualization platform on which to host virtual servers as either virtual machines or containers.This book will support your practice of the requisite skills to successfully create, tailor, and deploy virtual machines and containers with Proxmox VE 4.1. Following a survey of PVE's features and characteristics,this book will contrast containers with virtual machines and establish cases for both. It walks through the installation of Proxmox VE, explores the creation of containers and virtual machines, and suggests best practices for virtual disk creation, network configuration, and Proxmox VE host and guest security.Throughout the book, you will navigate the Proxmox VE 4.1 web interface and explore options for command-linemanagement

LEARNING PUPPET. Build intelligent software stacks with the Puppet configuration management suite

Jussi Heinonen

Puppet is a cross-platform, open source configuration management utility, which runs on various Unix, Linux, and Windows Microsoft platforms. It allows you to automate all your IT configurations, giving you control of what you do to each node, and also when and how you do it. You’ll be able to build and manage development, test, and production environments independently without requiring previous system administration experience.Learning Puppet is a step-by-step guide on how to get started with Puppet development and use Puppet modules as the building blocks to deploy production-ready application cluster in virtual environment.You will begin with the installation of development environment on the VirtualBox hypervisor and Puppet Learning VM that will be used as the platform for testing and development of Puppet modules. Next, you will learn how to manage virtual machines and snapshots effectively and enhance the development experience with advanced VirtualBox features.Later the book will focus on Puppet module development in detail. You will be guided through the process of utilizing existing modules that are available in the public module repository, write your own modules and use them to deploy a real-world web application that includes features such as monitoring and load balancing. You will then learn to scale your environment and turn your static configuration into a dynamic one through stored configurations and PuppetDB. Finally, the book will provide you with practical advice on Puppet troubleshooting and managing your environment with the wealth of features provided by the Puppet Enterprise console.

Learning Puppet for Windows Server. Organize your Windows environment using Puppet tools to unload administrative burdens in a short time!

Fuat Ulugay

Puppet is a configuration management tool. It allows you to automate all your IT configurations by giving you control of what you do to each “node” (Puppet agent), focusing also on when and how you do it. In context, Puppet is a cross-platform tool that is widely used for Unix-like and Microsoft Windows systems declaratively. However, it has been used more popularly for Unix-like systems. This book provides insights into using Puppet for Windows administration tasks such as server setup, application updates, and service management.This book kicks off with the fundamentals of Puppet by helping you with the installation of Puppet on a Windows server and progresses with the introduction of the Foreman interface for managing Puppet nodes. Next, you deal with the installation of Puppet agents on multiple clients and how to connect them to your Puppet server by grouping your nodes for easy management. You then become familiarized with the scripting of Puppet manifests along with an understanding of the module structure in Puppet. You further move on to the installation of Puppet Forge Modules and their usage in Windows along with advanced topics such as facts, functions and templates.Moreover, you also venture into the security aspects for Windows by gaining insights into various security settings that will make your server and clients more secure from hackers using different attack vectors. You will also use Puppet and Chocolatey to install and update software.You finally round off by learning how to check the details of reporting and status monitoring along with the automation of installing and updating software for multiple Windows clients arming you with ample artillery to tame Puppet for your future projects.

Learning Puppet Security. Secure your IT environments with the powerful security tools of Puppet

Jason Slagle

If you are a security professional whose workload is increasing, or a Puppet professional looking to increase your knowledge of security, or even an experienced systems administrator, then this book is for you. This book will take you to the next level of security automation using Puppet. The book requires no prior knowledge of Puppet to get started.

Learning PySpark. Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0

Tomasz Drabas, Denny Lee

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.