Видавець: 16

Learning PowerShell DSC. Automate deployment and configuration of your servers - Second Edition

James Pogran

The main goal of this book is to teach you to configure, deploy, and manage your system using the new features of PowerShell v5/v6 DSC.This book begins with the basics of PowerShell Desired State Configuration, covering its architecture and components. It familiarizes you with the set of Windows PowerShell language extensions and new Windows PowerShell commands that make up DSC. Then it helps you create DSC custom resources and work with DSC configurations with the help of practical examples. Finally, it describes how to deploy configuration data using PowerShell DSC. Throughout this book, we will be focusing on concepts such as building configurations with parameters, the local configuration manager, and testing and restoring configurations using PowerShell DSC.By the end of the book, you will be able to deploy a real-world application end-to-end and will be familiar enough with the powerful Desired State Configuration platform to achieve continuous delivery and efficiently and easily manage and deploy data for systems.

Learning Powershell DSC. Get started with the fundamentals of PowerShell DSC and utilize its power to automate deployment and configuration of your servers

James Pogran

Windows PowerShell is a task-based command-line shell and scripting language designed especially for system administration. PowerShell DSC is a new management platform that enables you to deploy and manage configuration data for software services and manage the environment in which these services run.This book begins with an overview of the basics of PowerShell DSC by covering the architecture and components of the Desired Sate Configuration. It will then familiarize you with the set of PowerShell language extensions and new PowerShell commands. It will help you understand and create DSC configurations with the help of practical examples, and to create DSC custom resources for your custom applications. Finally, you will learn to deploy a real world application using PowerShell DSC. By the end of the book, you will have better knowledge about the powerful Desired State Configuration platform, which helps you to achieve continuous delivery, and efficient management and easy deployment of data for systems.

Learning Predictive Analytics with Python. Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Ashish Kumar

Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You’ll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world.

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.