Build safety-critical and memory-safe stand-alone and networked embedded systems Key Features * Know how C++ works and compares to other languages used for embedded development * Create advanced GUIs for embedded devices to design an attractive and functional UI * Integrate proven strategies into your design for optimum hardware performance Book Description C++ is a great choice for embedded development, most notably, because it does not add any bloat, extends maintainability, and offers many advantages over different programming languages. Hands-On Embedded Programming with C++17 will show you how C++ can be used to build robust and concurrent systems that leverage the available hardware resources. Starting with a primer on embedded programming and the latest features of C++17, the book takes you through various facets of good programming. You’ll learn how to use the concurrency, memory management, and functional programming features of C++ to build embedded systems. You will understand how to integrate your systems with external peripherals and efficient ways of working with drivers. This book will also guide you in testing and optimizing code for better performance and implementing useful design patterns. As an additional benefit, you will see how to work with Qt, the popular GUI library used for building embedded systems. By the end of the book, you will have gained the confidence to use C++ for embedded programming. What you will learn * Choose the correct type of embedded platform to use for a project * Develop drivers for OS-based embedded systems * Use concurrency and memory management with various microcontroller units (MCUs) * Debug and test cross-platform code with Linux * Implement an infotainment system using a Linux-based single board computer * Extend an existing embedded system with a Qt-based GUI * Communicate with the FPGA side of a hybrid FPGA/SoC system Who this book is for If you want to start developing effective embedded programs in C++, then this book is for you. Good knowledge of C++ language constructs is required to understand the topics covered in the book. No knowledge of embedded systems is assumed.

Explore the new and improved Jira 8 features such as agile board and advanced search for efficient project management Key Features * Work on agile projects in Jira from both the administrator and end user's perspective * Explore the improved Scrum and Kanban board and backlog * Work through exercises at the end of each chapter to reinforce your skills Book Description Atlassian Jira enables effective bug tracking for your software and mobile applications and provides tools to track and manage tasks for your projects. Jira Essentials is a comprehensive guide, now updated to Jira 8 to include enhanced features such as updates to Scrum and Kanban UI, additional search capabilities, and changes to Jira Service Desk. The book starts by explaining how to plan and set up a new Jira 8 instance from scratch before getting you acquainted with key features such as emails, workflows, business processes, and much more. You'll then understand Jira's data hierarchy and how to design and work with projects. Since Jira is used for issue management, this book delves into the different issues that can arise in your projects. You’ll explore fields, including custom fields, and learn to use them for more effective data collection. You’ll create new screens from scratch and customize them to suit your requirements. The book also covers workflows and business processes, and guides you in setting up incoming and outgoing mail servers. Toward the end, you’ll study Jira's security model and Jira Service Desk, which allows you to run Jira as a support portal. By the end of this Jira book, you will be able to implement Jira 8 in your projects with ease. What you will learn * Understand Jira's data hierarchy and how to design and work with projects in Jira * Use Jira for agile software projects, business process management, customer service support, and more * Understand issues and work with them * Design both system and custom fields to behave differently under different contexts * Create and design your own screens and apply them to different project and issue types * Gain an understanding of the workflow and its various components * Set up both incoming and outgoing mail servers to work with e-mails Who this book is for This book will be especially useful for project managers but it's also intended for other Jira users, including developers, and any other industry besides software development, who would like to leverage Jira's powerful task management and workflow features to better manage their business processes.

Master shell basics and Unix tools and discover easy commands to perform complex tasks with speed Key Features *Learn why the Bash shell is widely used on Linux and iOS *Explore advanced shell concepts, such as pipes and redirection *Understand how to use Unix command-line tools as building blocks for different tasks Book Description The most basic interface to a computer—the command line—remains the most flexible and powerful way of processing data and performing and automating various day-to-day tasks. Command Line Fundamentals begins by exploring the basics, and then focuses on the most common tool, the Bash shell (which is standard on all Linux and iOS systems). As you make your way through the book, you'll explore the traditional Unix command-line programs as implemented by the GNU project. You'll also learn to use redirection and pipelines to assemble these programs to solve complex problems. By the end of this book, you'll have explored the basics of shell scripting, allowing you to easily and quickly automate tasks. What you will learn *Use the Bash shell to run commands *Utilize basic Unix utilities such as cat, tr, sort, and uniq *Explore shell wildcards to manage groups of files *Apply useful keyboard shortcuts in shell *Employ redirection and pipes to process data *Write both basic and advanced shell scripts to automate tasks Who this book is for Command Line Fundamentals is for programmers who use GUIs but want to understand how to use the command line to complete tasks faster.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features *Master the art of real-time big data processing and machine learning *Explore a wide range of use-cases to analyze large data *Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: *Mastering Apache Spark 2.x by Romeo Kienzler *Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla *Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn *Get to grips with all the features of Apache Spark 2.x *Perform highly optimized real-time big data processing *Use ML and DL techniques with Spark MLlib and third-party tools *Analyze structured and unstructured data using SparkSQL and GraphX *Understand tuning, debugging, and monitoring of big data applications *Build scalable and fault-tolerant streaming applications *Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key Features *Make a hands-on start in the fields of Big Data, Distributed Technologies and Machine Learning *Learn how to design, develop and interpret the results of common Machine Learning algorithms *Uncover hidden patterns in your data in order to derive real actionable insights and business value Book Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learn *Understand how Spark fits in the context of the big data ecosystem *Understand how to deploy and configure a local development environment using Apache Spark *Understand how to design supervised and unsupervised learning models *Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries *Design real-time machine learning pipelines in Apache Spark *Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms Who this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key Features *Solve practical large data and processing challenges with Kafka *Tackle data processing challenges like late events, windowing, and watermarking *Understand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQL Book Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learn *How to validate data with Kafka *Add information to existing data ?ows *Generate new information through message composition *Perform data validation and versioning with the Schema Registry *How to perform message Serialization and Deserialization *How to perform message Serialization and Deserialization *Process data streams with Kafka Streams *Understand the duality between tables and streams with KSQL Who this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.

Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key Features *Implement image classification and object detection using machine learning and deep learning *Perform image classification, object detection, image segmentation, and other Computer Vision tasks *Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn *Install and run major Computer Vision packages within Python *Apply powerful support vector machines for simple digit classification *Understand deep learning with TensorFlow *Build a deep learning classifier for general images *Use LSTMs for automated image captioning *Read text from real-world images *Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

A journey toward containerized applications in production with a cloud-portable, secure, robust and highly available Docker Enterprise platform. Key Features * Get an insider’s view into the container movement and Docker Enterprise * Manage the transformation associated with enterprise container adoption * Walk through the enterprise container adoption journey Book Description While known mostly as the open source engine behind tens of millions of server nodes, Docker also offers commercially supported enterprise tooling known as the Docker Enterprise. This platform leverages the deep roots from Docker Engine - Community (formerly Docker CE) and Kubernetes, but adds support and tooling to efficiently operate a secure container platform at scale. With hundreds of enterprises on board, best practices and adoption patterns are emerging rapidly. These learning points can be used to inform adopters and help manage the enterprise transformation associated with enterprise container adoption. This book starts by explaining the case for Docker Enterprise, as well as its structure and reference architecture. From there, we progress through the PoC,pilot and production stages as a working model for adoption, evolving the platform’s design and configuration for each stage and using detailed application examples along the way to clarify and demonstrate important concepts.The book concludes with Docker’s impact on other emerging software technologies, such as Blockchain and Serverless computing. By the end of this book, you’ll have a better understanding of what it takes to get your enterprise up and running with Docker Enterprise and beyond. What you will learn * Understand why containers are important to an enterprise * Understand the features and components of Docker Enterprise 2 * Find out about the PoC, pilot, and production adoption phases * Get to know the best practices for installing and operating Docker Enterprise * Understand what is important for a Docker Enterprise in production * Run Kubernetes on Docker Enterprise Who this book is for This book is for Software Architects, DevOps Engineers, Tech Ops, Docker professionals, or any IT professional working with Docker and containers who wants to move containerized workloads to production. This book discusses the enterprise adoption of Docker and Kubernetes,therefore a basic understanding of Docker concepts will be helpful.

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Grasp advanced PowerShell Core 6.0 functionalities to automate your environment Key Features * Keep up with changes introduced in PowerShell Core 6.0 * Easily maintain appropriate compatibility with older versions * Automate complex tasks, manipulate data, and secure your environment with PowerShell Core 6.0 Book Description PowerShell scripts offer a handy way to automate various chores, however working effectively with these scripts can be a difficult task. This comprehensive guide starts with the fundamentals before moving on to advanced-level topics to help you become a PowerShell Core 6.0 expert. The first module, PowerShell Core 6.0 Fundamentals, begins with the new features of PowerShell Core 6.0, installing it on Linux, and working with parameters, objects and .NET classes from within PowerShell Core 6.0. As you make your way through the chapters, you'll see how to efficiently manage large amounts of data and interact with other services using PowerShell Core 6.0. You'll be able to make the most of PowerShell Core 6.0's powerful automation feature, where you will have different methods available to parse data and manipulate regular expressions and Windows Management Instrumentation (WMI). After having explored automation, you will enter the extending PowerShell Core 6.0 module, covering asynchronous processing and desired state configuration. In the last module, you will learn to extend PowerShell Core 6.0 using advanced scripts and filters, and also debug issues along with working on error handling techniques. By the end of this book, you will be an expert in scripting with PowerShell Core 6.0. What you will learn * Optimize code through the use of functions, switches, and looping structures * Work with objects and operators to test and manipulate data * Parse and manipulate different data types * Create scripts and functions using PowerShell * Use jobs, events, and popular public modules which assist with implementing multithreading * Write .NET classes with ease within the PowerShell * Create and implement regular expressions in PowerShell scripts * Make use of advanced techniques to define and restrict the behavior of parameters Who this book is for If you are a system administrator who wants to become an expert in controlling and automating your Windows environment, then Mastering Windows PowerShell Scripting is for you. It is also ideal for those new to the PowerShell language.

Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features * Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more * Build your own neural network models using modern Python libraries * Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn * Use cluster algorithms to identify and optimize natural groups of data * Explore advanced non-linear and hierarchical clustering in action * Soft label assignments for fuzzy c-means and Gaussian mixture models * Detect anomalies through density estimation * Perform principal component analysis using neural network models * Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.

Master the TypeScript language and its latest features. Explore modern application frameworks and utilize industry best practices in TDD, OOP and UI Design. Key Features * Learn the key features of TypeScript 3 and explore advanced language features through in-depth discussions. * Use TypeScript with modern frameworks including Backbone, Angular, Aurelia, React, and Node. * Explore TDD practices, OOP techniques, and industry best practices to create high-quality, modular, and adaptable applications. Book Description TypeScript is both a language and a set of tools to generate JavaScript. It was designed by Anders Hejlsberg at Microsoft to help developers write enterprise-scale JavaScript. Starting with an introduction to the TypeScript language, before moving on to basic concepts, each section builds on previous knowledge in an incremental and easy-to-understand way. Advanced and powerful language features are all covered, including asynchronous programming techniques, decorators, and generics. This book explores many modern JavaScript and TypeScript frameworks side by side in order for the reader to learn their respective strengths and weaknesses. It will also thoroughly explore unit and integration testing for each framework. Best-of-breed applications utilize well-known design patterns in order to be scalable, maintainable, and testable. This book explores some of these object-oriented techniques and patterns, and shows real-world implementations. By the end of the book, you will have built a comprehensive, end-to-end web application to show how TypeScript language features, design patterns, and industry best practices can be brought together in a real-world scenario. What you will learn * Gain insights into core and advanced TypeScript language features * Integrate existing JavaScript libraries and third-party frameworks using declaration files * Target popular JavaScript frameworks, such as Angular, React, and more * Create test suites for your application with Jasmine and Selenium * Organize your application code using modules, AMD loaders, and SystemJS * Explore advanced object-oriented design principles * Compare the various MVC implementations in Aurelia, Angular, React, and more Who this book is for This guide to the TypeScript that starts with basic concepts, and then builds on this knowledge to introduce more advanced language features and frameworks. No prior knowledge of JavaScript is required, although some prior programming experience is assumed. If you are keen to learn TypeScript, this book will give you all of the necessary knowledge and skills to tackle any TypeScript project. If you are already an experienced JavaScript or TypeScript developer, then this book will take your skills to the next level. Learn how to use TypeScript with a multitude of modern frameworks, and choose the best framework for your project requirements. Investigate techniques for Test Driven Development, explore industry-standard design patterns, and learn how to put together a full production-ready TypeScript application.

This is a practical certification guide covering all the exam topics in an easy-to-follow manner backed with self-assessment scenarios for better preparation. Key Features *A step-by-step guide to give you a clear understanding of the Network+ Certification *Learn about network architecture, protocols, security, and network troubleshooting *Confidently ace the N10-007 exam with the help of practice tests Book Description CompTIA certified professionals have always had the upper hand in the information technology industry. This book will be your ideal guide to efficiently passing and achieving this certification. Learn from industry experts and implement their practices to resolve complex IT issues. This book revolves around networking concepts where readers will learn topics like network architecture, security, network monitoring, and troubleshooting. This book will not only prepare the readers conceptually but will also help them pass the N10-007 exam. This guide will also provide practice exercise after every chapter where readers can ensure their concepts are clear. By the end of this book, readers will leverage this guide and the included practice questions to boost their confidence in appearing for the actual certificate. What you will learn *Explain the purpose of a variety of networking concepts and implement them appropriately *Understand physical security and common attacks while securing wired and wireless networks *Understand the fundamentals of IPv4 and IPv6 *Determine and explain the appropriate cabling, device, and storage technologies *Understand network troubleshooting methodology and appropriate tools to support connectivity and performance *Use best practices to manage the network, determine policies, and ensure business continuity Who this book is for This book is ideal for readers wanting to pass the CompTIA Network+ certificate. Rookie network engineers and system administrators interested in enhancing their networking skills would also benefit from this book. No Prior knowledge on networking would be needed.

Begin your iOS 12 app development journey with this practical guide Key Features *Kick-start your iOS programming career and have fun building iOS apps of your choice *Get to grips with Xcode 10 and Swift 4.2, the building blocks of iOS development *Discover the latest features of iOS 12 - SiriKit, notifications, and much more Book Description Want to build iOS 12 applications from scratch with the latest Swift 4.2 language and Xcode 10 by your side? Forget sifting through tutorials and blog posts; this book is a direct route to iOS development, taking you through the basics and showing you how to put principles into practice. Take advantage of this developer-friendly guide and start building applications that may just take the App Store by storm! If you’re already an experienced programmer, you can jump right in and learn the latest iOS 12 features. For beginners, this book starts by introducing you to iOS development as you learn Xcode and Swift. You'll also study advanced iOS design topics, such as gestures and animations, to give your app the edge. You’ll explore the latest Swift 4.2 and iOS 12 developments by incorporating new features, such as the latest in notifications, custom-UI notifications, maps, and the recent additions in Sirikit. The book will guide you in using TestFlight to quickly get to grips with everything you need to get your project on the App Store. By the end of this book, you'll be ready to start building your own cool iOS applications confidently. What you will learn *Explore the distinctive design principles that define the iOS user experience *Navigate panels within an Xcode project *Use the latest Xcode asset catalogue of Xcode 10 *Create a playgrounds project within your projects and understand how Ranges and Control flow work *Study operations with integers and work your way through if statements *Build a responsive UI and add privacy to your custom-rich notifications *Set up Sirikit to add voice for Siri shortcuts *Collect valuable feedback with TestFlight before releasing your apps on the App Store Who this book is for This book is for you if you are completely new to Swift, iOS, or programming and want to make iOS applications. However, you’ll also find this book useful if you’re an experienced programmer looking to explore the latest iOS 12 features.

Don't waste your energy thinking about servers; use AWS to build enterprise-grade serverless applications. Key Features *Learn how to quickly and easily go serverless *Explore AWS and Lambda: the first building blocks of serverless applications on AWS *Study different approaches to deploy and maintain serverless applications Book Description Serverless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You'll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda. This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You’ll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You'll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you’ll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight serverless architectures. By the end of the book, you will be ready to create and run your first serverless application that takes advantage of the high availability, security, performance, and scalability of AWS. What you will learn *Explore AWS services for supporting a serverless environment *Set up AWS services to make applications scalable and highly available *Deploy a static website with a serverless architecture *Build your first serverless web application *Study the changes in a deployed serverless web application *Apply best practices to ensure overall security, availability, and reliability Who this book is for This book is for you if you want to develop serverless applications and have some prior coding experience. Though no prior experience of AWS is needed, basic knowledge of Java or Node.js will be an added advantage.

Choose the smarter way to learn about containerizing your applications and running them in production. Key Features * Deploy and manage highly scalable, containerized applications with Kubernetes * Build high-availability Kubernetes clusters * Secure your applications via encapsulation, networks, and secrets Book Description Kubernetes is an open source orchestration platform for managing containers in a cluster environment. This Learning Path introduces you to the world of containerization, in addition to providing you with an overview of Docker fundamentals. As you progress, you will be able to understand how Kubernetes works with containers. Starting with creating Kubernetes clusters and running applications with proper authentication and authorization, you'll learn how to create high-availability Kubernetes clusters on Amazon Web Services (AWS), and also learn how to use kubeconfig to manage different clusters. Whether it is learning about Docker containers and Docker Compose, or building a continuous delivery pipeline for your application, this Learning Path will equip you with all the right tools and techniques to get started with containerization. By the end of this Learning Path, you will have gained hands-on experience of working with Docker containers and orchestrators, including SwarmKit and Kubernetes. This Learning Path includes content from the following Packt products: * Kubernetes Cookbook - Second Edition by Hideto Saito, Hui-Chuan Chloe Lee, and Ke-Jou Carol Hsu * Learn Docker - Fundamentals of Docker 18.x by Gabriel N. Schenker What you will learn * Build your own container cluster * Run a highly distributed application with Docker Swarm or Kubernetes * Update or rollback a distributed application with zero downtime * Containerize your traditional or microservice-based application * Build a continuous delivery pipeline for your application * Track metrics and logs for every container in your cluster * Implement container orchestration to streamline deploying and managing applications Who this book is for This beginner-level Learning Path is designed for system administrators, operations engineers, DevOps engineers, and developers who want to get started with Docker and Kubernetes. Although no prior experience with Docker is required, basic knowledge of Kubernetes and containers will be helpful.

Take your neural networks to a whole new level with the simplicity and modularity of Keras, the most commonly used high-level neural networks API. Key Features * Solve complex machine learning problems with precision * Evaluate, tweak, and improve your deep learning models and solutions * Use different types of neural networks to solve real-world problems Book Description Though designing neural networks is a sought-after skill, it is not easy to master. With Keras, you can apply complex machine learning algorithms with minimum code. Applied Deep Learning with Keras starts by taking you through the basics of machine learning and Python all the way to gaining an in-depth understanding of applying Keras to develop efficient deep learning solutions. To help you grasp the difference between machine and deep learning, the book guides you on how to build a logistic regression model, first with scikit-learn and then with Keras. You will delve into Keras and its many models by creating prediction models for various real-world scenarios, such as disease prediction and customer churning. You’ll gain knowledge on how to evaluate, optimize, and improve your models to achieve maximum information. Next, you’ll learn to evaluate your model by cross-validating it using Keras Wrapper and scikit-learn. Following this, you’ll proceed to understand how to apply L1, L2, and dropout regularization techniques to improve the accuracy of your model. To help maintain accuracy, you’ll get to grips with applying techniques including null accuracy, precision, and AUC-ROC score techniques for fine tuning your model. By the end of this book, you will have the skills you need to use Keras when building high-level deep neural networks. What you will learn * Understand the difference between single-layer and multi-layer neural network models * Use Keras to build simple logistic regression models, deep neural networks, recurrent neural networks, and convolutional neural networks * Apply L1, L2, and dropout regularization to improve the accuracy of your model * Implement cross-validate using Keras wrappers with scikit-learn * Understand the limitations of model accuracy Who this book is for If you have basic knowledge of data science and machine learning and want to develop your skills and learn about artificial neural networks and deep learning, you will find this book useful. Prior experience of Python programming and experience with statistics and logistic regression will help you get the most out of this book. Although not necessary, some familiarity with the scikit-learn library will be an added bonus.

Understand Gang of Four, architectural, functional, and reactive design patterns and how to implement them on modern Java platforms, such as Java 12 and beyond Key Features * Learn OOP, functional, and reactive patterns for creating readable and maintainable code * Explore architectural patterns and practices for building scalable and reliable applications * Tackle all kinds of performance-related issues and streamline development using design patterns Book Description Java design patterns are reusable and proven solutions to software design problems. This book covers over 60 battle-tested design patterns used by developers to create functional, reusable, and flexible software. Hands-On Design Patterns with Java starts with an introduction to the Unified Modeling Language (UML), and delves into class and object diagrams with the help of detailed examples. You'll study concepts and approaches to object-oriented programming (OOP) and OOP design patterns to build robust applications. As you advance, you'll explore the categories of GOF design patterns, such as behavioral, creational, and structural, that help you improve code readability and enable large-scale reuse of software. You’ll also discover how to work effectively with microservices and serverless architectures by using cloud design patterns, each of which is thoroughly explained and accompanied by real-world programming solutions. By the end of the book, you’ll be able to speed up your software development process using the right design patterns, and you’ll be comfortable working on scalable and maintainable projects of any size. What you will learn * Understand the significance of design patterns for software engineering * Visualize software design with UML diagrams * Strengthen your understanding of OOP to create reusable software systems * Discover GOF design patterns to develop scalable applications * Examine programming challenges and the design patterns that solve them * Explore architectural patterns for microservices and cloud development Who this book is for If you are a developer who wants to learn how to write clear, concise, and effective code for building production-ready applications, this book is for you. Familiarity with the fundamentals of Java is assumed.

A definitive guide covering all the core concepts necessary to pass the Salesforce Administrator Certification exam Key Features * Understand critical design considerations for setting up Salesforce CRM * Facilitate and manage the transition from Salesforce Classic to Lightning Experience * Learn key functions of application security to manage user profiles and data Book Description Salesforce’s winter ’19 release offers a host of new features for CRM designed to meet your sales and marketing requirements. With this comprehensive guide to implementing Salesforce CRM, administrators of all levels can easily get a thorough understanding of the platform. This Salesforce handbook begins by guiding you in setting up users and security and then progresses to configuration, data management, and data analytics. You’ll discover process automation and approval mechanisms, while also exploring the functional areas of Sales Cloud, Service Cloud, Marketing Cloud, and Salesforce Chatter. This book covers Salesforce CRM system administration in a practical way, and it’ll serve as an invaluable reference for both new administrators and experienced professionals. Furthermore, you’ll also delve into Salesforce mobile apps and mobile administration, along with Salesforce Adoption Manager. You’ll gain insights into Lightning Experience, Salesforce's new app, and learn how its modern design and sleek interface helps you to build customizable components. Finally, we'll see how the two versions compare and help manage the transition from Salesforce Classic to Lightning Experience.?? By the end of the book, you will have mastered the techniques to configure and control various user interface features in Salesforce CRM. What you will learn * Configure a variety of user interface features in Salesforce CRM * Understand the capabilities of the Salesforce CRM sharing model * Explore Einstein Analytics - Salesforce's new wave of advanced reporting * Get to grips with the Lightning Process Builder workflow * Set up user profiles, security, and login access mechanisms * Find out how Apex and Visualforce coding can be used in Salesforce CRM * Manage the transition from Salesforce Classic to Lightning Experience * Implement data manipulation features to apply best practices in data management Who this book is for This book is for administrators who want to develop and strengthen their Salesforce CRM skills in the areas of configuration and system management. Whether you are a new or experienced professional, this book will enhance your knowledge and understanding of Salesforce CRM features.

Learn how to write automated tests for Dynamics 365 Business Central and see how to implement it in your daily work Key Features * Leverage automated testing to advance over traditional manual testing methods * Write, design, and implement automated tests * Explore various testing frameworks and tools compatible with Microsoft Dynamics 365 Business Central Book Description Dynamics 365 Business Central is the new cloud-based SaaS ERP proposition from Microsoft. It’s not as simple as it used to be way back when it was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision. Our development practices are becoming more formal, and with this, the call for test automation is pressing on us. This book will teach you to leverage testing tools available with Dynamics 365 Business Central to perform automated testing. We’ll begin with a quick introduction to automated testing, followed by an overview of test automation in Dynamics 365 Business Central. Then you’ll learn to design and build automated tests and we’ll go through some efficient methods to get from requirements to application and testing code. Lastly, you’ll learn to incorporate your own and Microsoft tests into your daily development practice. By the end of the book, you’ll be able to write your own automated tests for Dynamics 365 Business Central. What you will learn * Understand what automated tests are, and when and why to use them * Explore the five pillars of the Testability Framework of Business Central * Design and write automated tests for Business Central * Make use of standard automated tests and their helper libraries * Integrate automated tests into your development practice Who this book is for This book is for consultants, testers, developers, and development managers working with Microsoft Dynamics NAV and Business Central. Being a book on automated testing techniques, it also caters to both functional and technical development teams.