Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data Key Features * A beginner's guide for performing data analysis loaded with numerous rich, practical examples * Access to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysis * Develop applications in Scala for real-time analysis and machine learning in Apache Spark Book Description Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights What you will learn * Techniques to determine the validity and confidence level of data * Apply quartiles and n-tiles to datasets to see how data is distributed into many buckets * Create data pipelines that combine multiple data lifecycle steps * Use built-in features to gain a deeper understanding of the data * Apply Lasso regression analysis method to your data * Compare Apache Spark API with traditional Apache Spark data analysis Who this book is for If you are a data scientist or a data analyst who wants to learn how to perform data analysis using Scala, this book is for you. All you need is knowledge of the basic fundamentals of Scala programming.

Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features * Get to grips with the fundamentals of deep learning and neural networks * Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing * Implement effective deep learning systems in R with the help of end-to-end projects Book Description Deep learning finds practical applications in several domains, while R is the preferred language for designing and deploying deep learning models. This Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you’ll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The book will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you’ll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R. By the end of this Learning Path, you’ll be well versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects. This Learning Path includes content from the following Packt products: * R Deep Learning Essentials - Second Edition by F. Wiley and Mark Hodnett * R Deep Learning Projects by Yuxi (Hayden) Liu and Pablo Maldonado What you will learn * Implement credit card fraud detection with autoencoders * Train neural networks to perform handwritten digit recognition using MXNet * Reconstruct images using variational autoencoders * Explore the applications of autoencoder neural networks in clustering and dimensionality reduction * Create natural language processing (NLP) models using Keras and TensorFlow in R * Prevent models from overfitting the data to improve generalizability * Build shallow neural network prediction models Who this book is for This Learning Path is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. A fundamental understanding of R programming and familiarity with the basic concepts of deep learning are necessary to get the most out of this Learning Path.

A comprehensive guide to building full stack applications covering frontend and server-side programming, data management, and web security Key Features * Unleash the power of React Hooks to build interactive and complex user interfaces * Build scalable full stack applications designed to meet demands of modern users * Understand how the Axios library simplifies CRUD operations Book Description React Hooks have changed the way React components are coded. They enable you to write components in a more intuitive way without using classes, which makes your code easier to read and maintain. Building on from the previous edition, this book is updated with React Hooks and the latest changes introduced in create-react-app and Spring Boot 2.1. This book starts with a brief introduction to Spring Boot. You’ll understand how to use dependency injection and work with the data access layer of Spring using Hibernate as the ORM tool. You’ll then learn how to build your own RESTful API endpoints for web applications. As you advance, the book introduces you to other Spring components, such as Spring Security to help you secure the backend. Moving on, you’ll explore React and its app development environment and components for building your frontend. Finally, you’ll create a Docker container for your application by implementing the best practices that underpin professional full stack web development. By the end of this book, you’ll be equipped with all the knowledge you need to build modern full stack applications with Spring Boot for the backend and React for the frontend. What you will learn * Create a RESTful web service with Spring Boot * Grasp the fundamentals of dependency injection and how to use it for backend development * Discover techniques for securing the backend using Spring Security * Understand how to use React for frontend programming * Benefit from the Heroku cloud server by deploying your application to it * Delve into the techniques for creating unit tests using JUnit * Explore the Material UI component library to make more user-friendly user interfaces Who this book is for If you are a Java developer familiar with Spring, but are new to building full stack applications, this is the book for you.

Understand the nitty-gritty of Cybersecurity with ease Key Features * Align your security knowledge with industry leading concepts and tools * Acquire required skills and certifications to survive the ever changing market needs * Learn from industry experts to analyse, implement, and maintain a robust environment Book Description It's not a secret that there is a huge talent gap in the cybersecurity industry. Everyone is talking about it including the prestigious Forbes Magazine, Tech Republic, CSO Online, DarkReading, and SC Magazine, among many others. Additionally, Fortune CEO's like Satya Nadella, McAfee's CEO Chris Young, Cisco's CIO Colin Seward along with organizations like ISSA, research firms like Gartner too shine light on it from time to time. This book put together all the possible information with regards to cybersecurity, why you should choose it, the need for cyber security and how can you be part of it and fill the cybersecurity talent gap bit by bit. Starting with the essential understanding of security and its needs, we will move to security domain changes and how artificial intelligence and machine learning are helping to secure systems. Later, this book will walk you through all the skills and tools that everyone who wants to work as security personal need to be aware of. Then, this book will teach readers how to think like an attacker and explore some advanced security methodologies. Lastly, this book will deep dive into how to build practice labs, explore real-world use cases and get acquainted with various cybersecurity certifications. By the end of this book, readers will be well-versed with the security domain and will be capable of making the right choices in the cybersecurity field. What you will learn * Get an overview of what cybersecurity is and learn about the various faces of cybersecurity as well as identify domain that suits you best * Plan your transition into cybersecurity in an efficient and effective way * Learn how to build upon your existing skills and experience in order to prepare for your career in cybersecurity Who this book is for This book is targeted to any IT professional who is looking to venture in to the world cyber attacks and threats. Anyone with some understanding or IT infrastructure workflow will benefit from this book. Cybersecurity experts interested in enhancing their skill set will also find this book useful.

Plan and build useful machine learning systems for financial services, with full working Python code Key Features * Build machine learning systems that will be useful across the financial services industry * Discover how machine learning can solve finance industry challenges * Gain the machine learning insights and skills fintech companies value most Book Description Machine learning skills are essential for anybody working in financial data analysis. Machine Learning for Finance shows you how to build machine learning models for use in financial services organizations. It shows you how to work with all the key machine learning models, from simple regression to advanced neural networks. You will see how to use machine learning to automate manual tasks, identify and address systemic bias, and find new insights and patterns hidden in available data. Machine Learning for Finance encourages and equips you to find new ways to use data to serve an organization’s business goals. Broad in scope yet deeply practical in approach, Machine Learning for Finance will help you to apply machine learning in all parts of a financial organization’s infrastructure. If you work or plan to work in fintech, and want to gain one of the most valuable skills in the sector today, this book is for you. What you will learn * Practical machine learning for the finance sector * Build machine learning systems that support the goals of financial organizations * Think creatively about problems and how machine learning can solve them * Identify and reduce sources of bias from machine learning models * Apply machine learning to structured data, natural language, photographs, and written text related to finance * Use machine learning to detect fraud, forecast financial trends, analyze customer sentiments, and more * Implement heuristic baselines, time series, generative models, and reinforcement learning in Python, scikit-learn, Keras, and TensorFlow Who this book is for Machine Learning for Finance is for financial professionals who want to develop and apply machine learning skills, and for students entering the field. You should be comfortable with Python and the basic data science stack, such as NumPy, pandas, and Matplotlib, to get the most out of this book.

This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key Features * Your handy guide to building machine learning workflows in Go for real-world scenarios * Build predictive models using the popular supervised and unsupervised machine learning techniques * Learn all about deployment strategies and take your ML application from prototype to production ready Book Description Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go. The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced. The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum. The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring. At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones. What you will learn * Understand the types of problem that machine learning solves, and the various approaches * Import, pre-process, and explore data with Go to make it ready for machine learning algorithms * Visualize data with gonum/plot and Gophernotes * Diagnose common machine learning problems, such as overfitting and underfitting * Implement supervised and unsupervised learning algorithms using Go libraries * Build a simple web service around a model and use it to make predictions Who this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.

Build state-of-the-art web applications quickly and efficiently using Flask and related technologies with Python 3 Key Features * Updated to Flask 1.0.3 and Python 3.7 with coverage of Microservices * Get the most out of the powerful Flask framework and maintain the flexibility of your design choices * Write cleaner and maintainable code with the help of sample apps Book Description Flask, the lightweight Python web framework, is popular due to its powerful modular design that lets you build scalable web apps. With this recipe-based guide, you’ll explore modern solutions and best practices for Flask web development. Updated to the latest version of Flask and Python 3, this second edition of Flask Framework Cookbook moves away from some of the old and obsolete libraries and introduces recipes on bleeding edge technologies. You’ll discover different ways of using Flask to create, deploy, and manage microservices. This Flask Python book starts by covering the different configurations that a Flask application can make use of, and then helps you work with templates and learn about the ORM and view layers. You’ll also be able to write an admin interface and get to grips with debugging and logging errors. Finally, you’ll grasp a variety of deployment and post-deployment techniques for platforms such as Apache, Tornado, and Heroku. By the end of this book, you’ll have gained all the knowledge you need to write Flask applications in the best possible way and scale them using standard industry practices. What you will learn * Explore web application development in Flask, right from installation to post-deployment stages * Make use of advanced templating and data modeling techniques * Discover effective debugging, logging, and error handling techniques in Flask * Integrate Flask with different technologies such as Redis, Sentry, and MongoDB * Deploy and package Flask applications with Docker and Kubernetes * Design scalable microservice architecture using AWS LambdaContinuous integration and Continuous deployment Who this book is for If you are a web developer who wants to learn more about developing scalable and production-ready applications in Flask, this is the book for you. You’ll also find this book useful if you are already aware of Flask's major extensions and want to use them for better application development. Basic Python programming experience along with basic understanding of Flask is assumed.

Leverage the features of Azure SQL database and become an expert in data management Key Features * Explore ways to create shards and elastic pools to scale Azure SQL databases * Automate common management tasks with PowerShell * Implement over 40 practical activities and exercises to reinforce your learning Book Description Despite being the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. This book shows you how to administer Azure SQL database to fully benefit from its wide range of features and functionality. Professional Azure SQL Database Administration begins by covering the architecture and explaining the difference between Azure SQL Database and the on-premise SQL Server to help you get comfortable with Azure SQL database. You’ll perform common tasks such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you’ll study how you can save costs and manage and scale multiple SQL Databases using elastic pools. You’ll also implement a disaster recovery solution using standard and active geo-replication. Whether it is learning different techniques to monitor and tune an Azure SQL database or improving performance using in-memory technology, this book will enable you to make the most out of Azure SQL database features and functionality for data management solutions. By the end of this book, you’ll be well versed with key aspects of an Azure SQL database instance, such as migration, backup restorations, performance optimization, high availability, and disaster recovery. What you will learn * Understand Azure SQL Database configuration and pricing options * Provision a new SQL database or migrate an existing on-premise SQL Server database to Azure SQL Database * Back up and restore Azure SQL Database * Secure an Azure SQL database * Scale an Azure SQL database * Monitor and tune an Azure SQL database * Implement high availability and disaster recovery with Azure SQL Database * Automate common management tasks with PowerShell * Develop a scalable cloud solution with Azure SQL Database * Manage, maintain, and secure managed instances Who this book is for If you’re a database administrator, database developer, or an application developer interested in developing new applications or migrating existing ones with Azure SQL database, this book is for you. Prior experience of working with an on-premise SQL Server or Azure SQL database along with a basic understanding of PowerShell scripts and C# code is necessary to grasp the concepts covered in this book.

Learn to work with XRP and build applications on Ripple's blockchain Key Features *Learn to use Ripple’s decentralized system for transfering digital assets globally *A simpilfied and shortened learning curve to understand the Ripple innovation and Blockchain *Takes a hands-on approach to work with XRP – Ripple’s native currency Book Description This book starts by giving you an understanding of the basics of blockchain and the Ripple protocol. You will then get some hands-on experience of working with XRP. You will learn how to set up a Ripple wallet and see how seamlessly you can transfer money abroad. You will learn about different types of wallets through which you can store and transact XRP, along with the security precautions you need to take to keep your money safe. Since Ripple is currency agnostic, it can enable the transfer of value in USD, EUR, and any other currency. You can even transfer digital assets using Ripple. You will see how you can pay an international merchant with their own native currency and how Ripple can exchange it on the ?y. Once you understand the applications of Ripple, you will learn how to create a conditionally-held escrow using the Ripple API, and how to send and cash checks. Finally, you will also understand the common misconceptions people have about Ripple and discover the potential risks you must consider before making investment decisions. By the end of this book, you will have a solid foundation for working with Ripple's blockchain. Using it, you will be able to solve problems caused by traditional systems in your respective industry. What you will learn *Understand the fundamentals of blockchain and Ripple *Learn how to choose a Ripple wallet *Set up a Ripple wallet to send and receive XRP *Learn how to protect your XRP *Understand the applications of Ripple *Learn how to work with the Ripple API *Learn how to build applications on check and escrow features of Ripple Who this book is for This book is for anyone interested in getting their hands on Ripple technology and learn where it can be used to gain competitive advantages in their respective fields. For most parts of the book, you need not have any pre-requisite knowledge. However, you need to have basic background of JavaScript to write an escrow.

Leverage the power of Python, Ansible and other network automation tools to make your network robust and more secure Key Features *Get introduced to the concept of network automation with relevant use cases *Apply Continuous Integration and DevOps to improve your network performance *Implement effective automation using tools such as Python, Ansible, and more Book Description Network automation is the use of IT controls to supervise and carry out everyday network management functions. It plays a key role in network virtualization technologies and network functions. The book starts by providing an introduction to network automation, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and performing tasks such as ensuring golden state configurations using templates, interface parsing. This book also focuses on Intelligent Operations using Artificial Intelligence and troubleshooting using chatbots and voice commands. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation, including best practices in automation; ways to test automated networks using tools such as Puppet, SaltStack, and Chef; and other important techniques. Through practical use-cases and examples, this book will acquaint you with the various aspects of network automation. It will give you the solid foundation you need to automate your own network without any hassle. What you will learn *Get started with the fundamental concepts of network automation *Perform intelligent data mining and remediation based on triggers *Understand how AIOps works in operations *Trigger automation through data factors *Improve your data center's robustness and security through data digging *Get access infrastructure through API Framework for chatbot and voice interactive troubleshootings *Set up communication with SSH-based devices using Netmiko Who this book is for If you are a network engineer or a DevOps professional looking for an extensive guide to help you automate and manage your network efficiently, then this book is for you. No prior experience with network automation is required to get started, however you will need some exposure to Python programming to get the most out of this book.

Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping. Key Features * Use Go libraries like Goquery and Colly to scrape the web * Common pitfalls and best practices to effectively scrape and crawl * Learn how to scrape using the Go concurrency model Book Description Web scraping is the process of extracting information from the web using various tools that perform scraping and crawling. Go is emerging as the language of choice for scraping using a variety of libraries. This book will quickly explain to you, how to scrape data data from various websites using Go libraries such as Colly and Goquery. The book starts with an introduction to the use cases of building a web scraper and the main features of the Go programming language, along with setting up a Go environment. It then moves on to HTTP requests and responses and talks about how Go handles them. You will also learn about a number of basic web scraping etiquettes. You will be taught how to navigate through a website, using a breadth-first and then a depth-first search, as well as find and follow links. You will get to know about the ways to track history in order to avoid loops and to protect your web scraper using proxies. Finally the book will cover the Go concurrency model, and how to run scrapers in parallel, along with large-scale distributed web scraping. What you will learn * Implement Cache-Control to avoid unnecessary network calls * Coordinate concurrent scrapers * Design a custom, larger-scale scraping system * Scrape basic HTML pages with Colly and JavaScript pages with chromedp * Discover how to search using the "strings" and "regexp" packages * Set up a Go development environment * Retrieve information from an HTML document * Protect your web scraper from being blocked by using proxies * Control web browsers to scrape JavaScript sites Who this book is for Data scientists, and web developers with a basic knowledge of Golang wanting to collect web data and analyze them for effective reporting and visualization.

Discover the power of functional programming, lazy evaluation, monads, concurrency, and immutability to create succinct and expressive implementations Key Features * Get a solid understanding of how to apply functional programming concepts in TypeScript * Explore TypeScript runtime features such as event loop, closures, and Prototypes * Gain deeper knowledge on the pros and cons of TypeScript Book Description Functional programming is a powerful programming paradigm that can help you to write better code. However, learning functional programming can be complicated, and the existing literature is often too complex for beginners. This book is an approachable introduction to functional programming and reactive programming with TypeScript for readers without previous experience in functional programming with JavaScript, TypeScript , or any other programming language. The book will help you understand the pros, cons, and core principles of functional programming in TypeScript. It will explain higher order functions, referential transparency, functional composition, and monads with the help of effective code examples. Using TypeScript as a functional programming language, you’ll also be able to brush up on your knowledge of applying functional programming techniques, including currying, laziness, and immutability, to real-world scenarios. By the end of this book, you will be confident when it comes to using core functional and reactive programming techniques to help you build effective applications with TypeScript. What you will learn * Understand the pros and cons of functional programming * Delve into the principles, patterns, and best practices of functional and reactive programming * Use lazy evaluation to improve the performance of applications * Explore functional optics with Ramda * Gain insights into category theory functional data structures such as Functors and Monads * Use functions as values, so that they can be passed as arguments to other functions Who this book is for This book is designed for readers with no prior experience of functional programming with JavaScript, TypeScript or any other programming language. Some familiarity with TypeScript and web development is a must to grasp the concepts in the book easily.

Leverage the features and libraries of Python to administrate your environment efficiently. Key Features * Learn how to solve problems of system administrators and automate routine activities * Learn to handle regular expressions, network administration * Building GUI, web-scraping and database administration including data analytics Book Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learn * Understand how to install Python and debug Python scripts * Understand and write scripts for automating testing and routine administrative activities * Understand how to write scripts for text processing, encryption, decryption, and archiving * Handle files, such as pdf, excel, csv, and txt files, and generate reports * Write scripts for remote network administration, including handling emails * Build interactive tools using a graphical user interface * Handle Apache log files, SOAP and REST APIs communication * Automate database administration and perform statistical analysis Who this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features * Apply popular machine learning algorithms using a recipe-based approach * Implement boosting, bagging, and stacking ensemble methods to improve machine learning models * Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn * Understand how to use machine learning algorithms for regression and classification problems * Implement ensemble techniques such as averaging, weighted averaging, and max-voting * Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking * Use Random Forest for tasks such as classification and regression * Implement an ensemble of homogeneous and heterogeneous machine learning algorithms * Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed for data scientists, machine learning developers, and deep learning enthusiasts who want to delve into machine learning algorithms to build powerful ensemble models. Working knowledge of Python programming and basic statistics is a must to help you grasp the concepts in the book.

Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code Key Features * Build efficient and concurrent applications in Qt to create cross-platform applications * Identify performance bottlenecks and apply the correct algorithm to improve application performance * Delve into parallel programming and memory management to optimize your code Book Description Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance. The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you’ll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains. By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature What you will learn * Understand classic performance best practices * Get to grips with modern hardware architecture and its performance impact * Implement tools and procedures used in performance optimization * Grasp Qt-specific work techniques for graphical user interface (GUI) and platform programming * Make Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) performant and use the relevant Qt classes * Discover the improvements Qt 5.9 (and the upcoming versions) holds in store * Explore Qt's graphic engine architecture, strengths, and weaknesses Who this book is for This book is designed for Qt developers who wish to build highly performance applications for desktop and embedded devices. Programming Experience with C++ is required.

Learn best practices for testing with Jira and model industry workflows that can be used during the software development lifecycle Key Features * Integrate Jira with test management tools such as Zephyr, Test Management, and SynapseRT * Understand test case management, traceability, and test execution with reports * Implement continuous integration using Jira, Jenkins, and automated testing tools Book Description Hands-On Test Management with Jira begins by introducing you to the basic concepts of Jira and takes you through real-world software testing processes followed by various organizations. As you progress through the chapters, the book explores and compares the three most popular Jira plugins—Zephyr, Test Management, and synapseRT. With this book, you’ll gain a practical understanding of test management processes using Jira. You’ll learn how to create and manage projects, create Jira tickets to manage customer requirements, and track Jira tickets. You’ll also understand how to develop test plans, test cases, and test suites, and create defects and requirement traceability matrices, as well as generating reports in Jira. Toward the end, you’ll understand how Jira can help the SQA teams to use the DevOps pipeline for automating execution and managing test cases. You’ll get to grips with configuring Jira with Jenkins to execute automated test cases in Selenium. By the end of this book, you’ll have gained a clear understanding of how to model and implement test management processes using Jira. What you will learn * Understand QMS to effectively implement quality systems in your organization * Explore a business-driven structured approach to Test Management using TMap NEXT * Implement different aspects of test planning, test strategy, and test execution * Organize and manage Agile projects in Scrum and Kanban * Uncover Jira plugins available in the Atlassian Marketplace for testing and project management * Configure a DevOps pipeline for continuous integration using Jira with Jenkins Who this book is for If you’re a quality assurance professional, software project manager, or test manager interested in learning test management best practices in your team or organization, this book is for you. Prior knowledge of test management and Jenkins will be beneficial in understanding the concepts covered in this book.

Get to grips with the unified, highly scalable distributed storage system and learn how to design and implement it. Key Features * Explore Ceph's architecture in detail * Implement a Ceph cluster successfully and gain deep insights into its best practices * Leverage the advanced features of Ceph, including erasure coding, tiering, and BlueStore Book Description This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment. This Learning Path includes content from the following Packt products: * Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh * Mastering Ceph by Nick Fisk * Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh What you will learn * Understand the benefits of using Ceph as a storage solution * Combine Ceph with OpenStack, Cinder, Glance, and Nova components * Set up a test cluster with Ansible and virtual machine with VirtualBox * Develop solutions with Librados and shared object classes * Configure BlueStore and see its interaction with other configurations * Tune, monitor, and recover storage systems effectively * Build an erasure-coded pool by selecting intelligent parameters Who this book is for If you are a developer, system administrator, storage professional, or cloud engineer who wants to understand how to deploy a Ceph cluster, this Learning Path is ideal for you. It will help you discover ways in which Ceph features can solve your data storage problems. Basic knowledge of storage systems and GNU/Linux will be beneficial.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Unearth the power of GraphQL, React, Apollo, Node, and Express to build a scalable, production ready application Key Features * Build full stack applications with modern APIs using GraphQL and Apollo * Integrate Apollo into React and build frontend components using GraphQL * Implement a self-updating notification pop-up with a unique GraphQL feature called Subscriptions Book Description React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements. What you will learn * Resolve data from multi-table database and system architectures * Build a GraphQL API by implementing models and schemas with Apollo and Sequelize * Set up an Apollo Client and build front end components using React * Use Mocha to test your full-stack application * Write complex React components and share data across them * Deploy your application using Docker Who this book is for The book is for web developers who want to enhance their skills and build complete full stack applications using industry standards. Familiarity with JavaScript, React, and GraphQL is expected to get the most from this book.

Implement Business Central and explore methods to upgrade to NAV 2018 Key Features *Learn the key roles of Dynamics NAV partner and the roles within your customer's organization *Create configuration packages and perform data migration *Explore Microsoft Dynamics 365 Business Central to use Dynamics NAV 2018 functionalities in the Cloud Book Description Microsoft Dynamics Business Central is a full business solution suite and a complete ERP solution, which contains a robust set of development tools; these tools can help you to gain control over your business and can simplify supply chains, manufacturing, and operations. Implementing Microsoft Dynamics 365 Business Central On-Premise covers the latest features of Dynamics Business Central and NAV from the end users' and developers' perspectives. It also provides an insight into different tools available for implementation, whether it's a new installation or migrating from the previous version of Dynamics NAV. This book will take you from an introduction to Dynamics NAV 2018 through to exploring all the techniques related to implementation and migration. You will also learn to expand functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, and implement free third-party add-ons to your existing installation. As you progress through the book, you will learn to work with third-party add-on tools. In the concluding chapters, you will explore Dynamics 365 Business Central, the new Cloud solution based on the Microsoft NAV platform, and techniques for using Docker and Sandbox to develop applications. By the end of the book, you will have gained a deep understanding of the key components for successful Dynamics NAV implementation for an organization. What you will learn *Explore new features introduced in Microsoft Dynamics NAV 2018 *Migrate to Microsoft Dynamics NAV 2018 from previous versions *Learn abstract techniques for data analysis, reporting, and debugging *Install, configure, and use additional tools for business intelligence, document management, and reporting *Discover Dynamics 365 Business Central and several other Microsoft services *Utilize different tools to develop applications for Business Central Who this book is for Implementing Microsoft Dynamics 365 Business Central On-Premise is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementation. This book is for you if you want to be a project manager or get involved with Dynamics NAV, but do not have the expertise to write code yourself. This book can also help you to understand the need to move to Business Central and its advantages.

A definitive guide on frontend development with Angular from design to deployment Key Features *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles and RxJS to develop and test apps easily *Study continuous integration and deployment on the AWS cloud Book Description If you have been burnt by unreliable JavaScript frameworks before, you will be amazed by the maturity of the Angular platform. Angular enables you to build fast, efficient, and real-world web apps. In this Learning Path, you'll learn Angular and to deliver high-quality and production-grade Angular apps from design to deployment. You will begin by creating a simple fitness app, using the building blocks of Angular, and make your final app, Personal Trainer, by morphing the workout app into a full-fledged personal workout builder and runner with an advanced directive building - the most fundamental and powerful feature of Angular. You will learn the different ways of architecting Angular applications using RxJS, and some of the patterns that are involved in it. Later you’ll be introduced to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business apps, along with popular recipes. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patterns and practices to be successful as an individual developer on the web or as a team in the Enterprise. This Learning Path includes content from the following Packt products: *Angular 6 by Example by Chandermani Arora, Kevin Hennessy *Architecting Angular Applications with Redux, RxJS, and NgRx by Christoffer Noring *Angular 6 for Enterprise-Ready Web Applications by Doguhan Uluca What you will learn *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles, RxJS to develop and test apps efficiently *Study continuous integration and deployment your Angular app on the AWS cloud Who this book is for If you're a JavaScript or frontend developer looking to gain comprehensive experience of using Angular for end-to-end enterprise-ready applications, this Learning Path is for you.