Mastering Proxmox. Build virtualized environments using the Proxmox VE hypervisor - Third Edition

Wasim Ahmed

Proxmox is an open source server virtualization solution that has enterprise-class features for managing virtual machines, for storage, and to virtualize both Linux and Windows application workloads.You'll begin with a refresher on the advanced installation features and the Proxmox GUI to familiarize yourself with the Proxmox VE hypervisor. Then, you'll move on to explore Proxmox under the hood, focusing on storage systems, such as Ceph, used with Proxmox. Moving on, you'll learn to manage KVM virtual machines, deploy Linux containers fast, and see how networking is handled in Proxmox. You'll also learn how to protect a cluster or a VM with a firewall and explore the new high availability features introduced in Proxmox VE 5.0. Next, you'll dive deeper into the backup/restore strategy and see how to properly update and upgrade a Proxmox node. Later, you'll learn how to monitor a Proxmox cluster and all of its components using Zabbix. Finally, you'll discover how to recover Promox from disaster strikes through some real-world examples. By the end of the book, you'll be an expert at making Proxmox work in production environments with minimal downtime.

Hands-On Networking with Azure. Build large-scale, real-world apps using Azure networking solutions

Mohamed Waly

Microsoft Azure networking is one of the most valuable and important offerings in Azure. No matter what solution you are building for the cloud, you'll fi nd a compelling use for it. This book will get you up to speed quickly on Microsoft Azure Networking by teaching you how to use different networking services.By reading this book, you will develop a strong networking foundation for Azure virtual machines and for expanding your on-premise environment to Azure. Hands-On Networking with Azure starts with an introduction to Microsoft Azure networking and creating Azure Virtual Networks with subnets of different types within them. The book helps you understand the architecture of Azure networks. You will then learn the best practices for designing both Windows- and Linux-based Azure VM networks. You will also learn to expand your networks into Azure and how to use Azure DNS. Moreover, you will master best practices for dealing with Azure Load Balancer and the solutions they offer in different scenarios. Finally, we will demonstrate how the Azure Application Gateway works, offering various layer-7 load balancing capabilities for applications. By the end of this book, you will be able to architect your networking solutions for Azure.

Hands-On Android UI Development. Design and develop attractive user interfaces for Android applications

Jason Morris

A great user interface (UI) can spell the difference between success and failure for any new application. This book will show you not just how to code great UIs, but how to design them as well. It will take novice Android developers on a journey, showing them how to leverage the Android platform to produce stunning Android applications. Begin with the basics of creating Android applications and then move on to topics such as screen and layout design. Next, learn about techniques that will help improve performance for your application. Also, explore how to create reactive applications that are fast, animated, and guide the user toward their goals with minimal distraction. Understand Android architecture components and learn how to build your application to automatically respond to changes made by the user. Great platforms are not always enough, so this book also focuses on creating custom components, layout managers, and 2D graphics. Also, explore many tips and best practices to ease your UI development process. By the end, you'll be able to design and build not only amazing UIs, but also systems that provide the best possible user experience.

Learning Functional Programming in Go. Change the way you approach your applications using functional programming in Go

Lex Sheehan

Lex Sheehan begins slowly, using easy-to-understand illustrations and working Go code to teach core functional programming (FP) principles such as referential transparency, laziness, recursion, currying, and chaining continuations.This book is a tutorial for programmers looking to learn FP and apply it to write better code. Lex guides readers from basic techniques to advanced topics in a logical, concise, and clear progression.The book is divided into four modules. The first module explains the functional style of programming: pure functional programming, manipulating collections, and using higher-order functions. In the second module, you will learn design patterns that you can use to build FP-style applications. In the next module, you will learn FP techniques that you can use to improve your API signatures, increase performance, and build better cloud-native applications. The last module covers Category Theory, Functors, Monoids, Monads, Type classes and Generics.By the end of the book, you will be adept at building applications the FP way.

Machine Learning for OpenCV. Intelligent image processing with Python

Michael Beyeler

Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind.OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for.Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning.By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch!

IBM Watson Projects. Eight exciting projects that put artificial intelligence into practice for optimal business performance

James D. Miller

IBM Watson provides fast, intelligent insight in ways that the human brain simply can't match. Through eight varied projects, this book will help you explore the computing and analytical capabilities of IBM Watson.The book begins by refreshing your knowledge of IBM Watson's basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models. The projects covered in this book can be developed for different industries, including banking, healthcare, media, and security. These projects will enable you to develop an AI mindset and guide you in developing smart data-driven projects, including automating supply chains, analyzing sentiment in social media datasets, and developing personalized recommendations.By the end of this book, you'll have learned how to develop solutions for process automation, and you'll be able to make better data-driven decisions to deliver an excellent customer experience.

Blockchain Developer's Guide. Develop smart applications with Blockchain technologies - Ethereum, JavaScript, Hyperledger Fabric, and Corda

Brenn Hill, Samanyu Chopra, Paul Valencourt, Narayan Prusty

Blockchain applications provide a single-shared ledger to eliminate trust issues involving multiple stakeholders. It is the main technical innovation of Bitcoin, where it serves as the public ledger for Bitcoin transactions.Blockchain Developer's Guide takes you through the electrifying world of blockchain technology. It begins with the basic design of a blockchain and elaborates concepts, such as Initial Coin Offerings (ICOs), tokens, smart contracts, and other related terminologies. You will then explore the components of Ethereum, such as Ether tokens, transactions, and smart contracts that you need to build simple DApps.Blockchain Developer's Guide also explains why you must specifically use Solidity for Ethereum-based projects and lets you explore different blockchains with easy-to-follow examples. You will learn a wide range of concepts - beginning with cryptography in cryptocurrencies and including ether security, mining, and smart contracts. You will learn how to use web sockets and various API services for Ethereum. By the end of this Learning Path, you will be able to build efficient decentralized applications.This Learning Path includes content from the following Packt products:• Blockchain Quick Reference by Brenn Hill, Samanyu Chopra, Paul Valencourt• Building Blockchain Projects by Narayan Prusty

Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python

Sibanjan Das, Umit Mert Cakmak

AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.