Real-World Implementation of C# Design Patterns. Overcome daily programming challenges using elements of reusable object-oriented software

Bruce M. Van Horn II, Van Symons

As a software developer, you need to learn new languages and simultaneously get familiarized with the programming paradigms and methods of leveraging patterns, as both a communications tool and an advantage when designing well-written, easy-to-maintain code. Design patterns, being a collection of best practices, provide the necessary wisdom to help you overcome common sets of challenges in object-oriented design and programming.This practical guide to design patterns helps C# developers put their programming knowledge to work. The book takes a hands-on approach to introducing patterns and anti-patterns, elaborating on 14 patterns along with their real-world implementations. Throughout the book, you'll understand the implementation of each pattern, as well as find out how to successfully implement those patterns in C# code within the context of a real-world project.By the end of this design patterns book, you’ll be able to recognize situations that tempt you to reinvent the wheel, and quickly avoid the time and cost associated with solving common and well-understood problems with battle-tested design patterns.

Practical DevOps. Harness the power of DevOps to boost your skill set and make your IT organization perform better

joakim verona

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments. It stresses the cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.After a quick refresher to DevOps and continuous delivery, we quickly move on to looking at how DevOps affects architecture. You'll create a sample enterprise Java application that you’ll continue to work with through the remaining chapters. Following this, we explore various code storage and build server options. You will then learn how to perform code testing with a few tools and deploy your test successfully. Next, you will learn how to monitor code for any anomalies and make sure it’s running properly. Finally, you will discover how to handle logs and keep track of the issues that affect processes

Cardboard VR Projects for Android. Develop mobile virtual reality apps using the native Google Cardboard SDK for Android

Jonathan Linowes, Matt Schoen

Google Cardboard is a low-cost, entry-level media platform through which you can experience virtual reality and virtual 3D environments. Its applications are as broad and varied as mobile smartphone applications themselves. This book will educate you on the best practices and methodology needed to build effective, stable, and performant mobile VR applications.In this book, we begin by defining virtual reality (VR) and how Google Cardboard fits into the larger VR and Android ecosystem. We introduce the underlying scientific and technical principles behind VR, including geometry, optics, rendering, and mobile software architecture. We start with a simple example app that ensures your environment is properly set up to write, build, and run the app. Then we develop a reusable VR graphics engine that you can build upon. And from then on, each chapter is a self-contained project where you will build an example from a different genre of application, including a 360 degree photo viewer, an educational simulation of our solar system, a 3D model viewer, and a music visualizer.Given the recent updates that were rolled out at Google I/O 2016, the authors of Cardboard VR Projects for Android have collated some technical notes to help you execute the projects in this book with Google VR Cardboard Java SDK 0.8, released in May 2016. Refer to the article at https://www.packtpub.com/sites/default/files/downloads/GoogleVRUpdateGuideforCardbook.pdf which explains the updates to the source code of the projects.

Instant Testing with CasperJS. Create advanced and efficient CasperJS tests for your web development projects

Eric Brehault

Professional web development implies systematic testing. While JavaScript unit tests will validate your JavaScript library’s quality, web functional testing is the only way to guarantee the expected behavior of your web pages. CasperJS is a fast and simple JavaScript testing API that can run on any platform, and it is currently one of the best and easiest ways to write your functional tests.Instant Testing with CasperJS will teach you how to write efficient and accurate tests for your professional web developments. This practical guide explains the various different CasperJS principles through clear and detailed examples, covering a large set of common use cases. This book will progressively cover everything you need to know from CasperJS basic principles to the most advanced testing practices.This book starts off by introducing you to the different testing assertions that you can perform with the CasperJS API. We will then move on to cover why bad timing between event triggering can ruin tests and learn strategies to avoid it. Finally, you will learn how to test efficient and complex web interactions like drag and drop, authentication, and file uploading. With Instant Testing with CasperJS, you will be able to set up an advanced and functional test suite for your web development projects quickly and efficiently.

Machine Learning with R. Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data - Fourth Edition

Brett Lantz

Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data.You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data.

Mastering Azure Machine Learning. Execute large-scale end-to-end machine learning with Azure - Second Edition

Christoph Körner, Marcel Alsdorf

Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps.The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning.The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets.By the end of this book, you’ll be able to combine all the steps you’ve learned by building an MLOps pipeline.

R: Unleash Machine Learning Techniques. Smarter data analytics

Brett Lantz, Cory Lesmeister, Dipanjan Sarkar, Raghav Bali

R is the established language of data analysts and statisticians around the world. And you shouldn’t be afraid to use it…This Learning Path will take you through the fundamentals of R and demonstrate how to use the language to solve a diverse range of challenges through machine learning. Accessible yet comprehensive, it provides you with everything you need to become more a more fluent data professional, and more confident with R. In the first module you’ll get to grips with the fundamentals of R. This means you’ll be taking a look at some of the details of how the language works, before seeing how to put your knowledge into practice to build some simple machine learning projects that could prove useful for a range of real world problems.For the following two modules we’ll begin to investigate machine learning algorithms in more detail. To build upon the basics, you’ll get to work on three different projects that will test your skills. Covering some of the most important algorithms and featuring some of the most popular R packages, they’re all focused on solving real problems in different areas, ranging from finance to social media.This Learning Path has been curated from three Packt products:• R Machine Learning By Example By Raghav Bali, Dipanjan Sarkar• Machine Learning with R - Second Edition By Brett Lantz• Mastering Machine Learning with R By Cory Lesmeister

Ceph Cookbook. Over 100 effective recipes to help you design, implement, and manage the software-defined and massively scalable Ceph storage system

Karan Singh, Andreas Jaeger, Richard Siggs

Ceph is a unified, distributed storage system designed for excellent performance, reliability, and scalability. This cutting-edge technology has been transforming the storage industry, and is evolving rapidly as a leader in software-defined storage space, extending full support to cloud platforms such as Openstack and Cloudstack, including virtualization platforms. It is the most popular storage backend for Openstack, public, and private clouds, so is the first choice for a storage solution. Ceph is backed by RedHat and is developed by a thriving open source community of individual developers as well as several companies across the globe.This book takes you from a basic knowledge of Ceph to an expert understanding of the most advanced features, walking you through building up a production-grade Ceph storage cluster and helping you develop all the skills you need to plan, deploy, and effectively manage your Ceph cluster. Beginning with the basics, you’ll create a Ceph cluster, followed by block, object, and file storage provisioning. Next, you’ll get a step-by-step tutorial on integrating it with OpenStack and building a Dropbox-like object storage solution. We’ll also take a look at federated architecture and CephFS, and you’ll dive into Calamari and VSM for monitoring the Ceph environment. You’ll develop expert knowledge on troubleshooting and benchmarking your Ceph storage cluster. Finally, you’ll get to grips with the best practices to operate Ceph in a production environment.