Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda About This Book ? Use Anaconda to find solutions for clustering, classification, and linear regression ? Analyze your data efficiently with the most powerful data science stack ? Use the Anaconda cloud to store, share, and discover projects and libraries Who This Book Is For Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It’s also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected. What You Will Learn ? Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda ? Use the package manager conda and discover, install, and use functionally efficient and scalable packages ? Get comfortable with heterogeneous data exploration using multiple languages within a project ? Perform distributed computing and use Anaconda Accelerate to optimize computational powers ? Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud ? Tackle advanced data prediction problems In Detail Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R. Style and approach This book is your step-by-step guide full of use cases, examples and illustrations to get you well-versed with the concepts of Anaconda.

Optimize the powerful techniques of Java 9 to boost your application's performance About This Book ? Tackle all kinds of performance-related issues and streamline your development ? Dive into the new features of Java 9 ? Implement highly efficient and reliable codes with the help of new APIs of Java ? Embedded with assessments that will help you revise the concepts you have learned in this book Who This Book Is For This book is targeted at developers who would like to build reliable and high-performance applications with Java. What You Will Learn ? Familiarize with modular development and its impact on performance ? Learn various string-related performance improvements, including compact string and modify string concatenation ? Explore various underlying compiler improvements, such as tiered attribution and Ahead-of-Time (AOT) compilation ? Learn security manager improvements ? Understand enhancements in graphics rasterizers ? Use of command-line tools to speed up application development ? Learn how to implement multithreading and reactive programming ? Build microservices in Java 9 ? Implement APIs to improve application code In Detail Java 9 which is one of the most popular application development languages. The latest released version Java 9 comes with a host of new features and new APIs with lots of ready to use components to build efficient and scalable applications. Streams, parallel and asynchronous processing, multithreading, JSON support, reactive programming, and microservices comprise the hallmark of modern programming and are now fully integrated into the JDK. This book focuses on providing quick, practical solutions to enhance your application's performance. You will explore the new features, APIs, and various tools added in Java 9 that help to speed up the development process. You will learn about jshell, Ahead-of-Time (AOT) compilation, and the basic threads related topics including sizing and synchronization. You will also explore various strategies for building microservices including container-less, self-contained, and in-container. This book is ideal for developers who would like to build reliable and high-performance applications with Java. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. Style and approach This book is a fast-paced guide that provides practical solutions to enhance your application’s performance. Note: This book is a blend of text and quizzes, all packaged up keeping your journey in mind. It includes content from the following Packt product: ? Java 9 High Performance by Mayur Ramgir and Nick Samoylov

Build cross-platform solutions with .NET Core 2.0 through real-life scenarios About This Book ? Bridges the gap between learning and doing and improves your software development skills ? Covers the best practices of .NET development to improve your productivity ? Example-based approach to get you started quickly with software programming Who This Book Is For If you are a developer or architect and want to learn how to build cross-platform solutions using Microsoft .NET Core, this book is for you. It is assumed that you have some knowledge of the .NET Framework, OOP, and C# (or a similar programming language). What You Will Learn ? Build cross-platform applications with ASP.NET Core 2.0 and its tools ? Integrate, host, and deploy web apps with the cloud (Microsoft Azure) ? Leverage the ncurses native library to extend console capabilities in .NET Core on Linux and interop with native coden .NET Core on Linux and learn how to interop with existing native code ? Reuse existing .NET Framework and Mono assemblies from .NET Core 2.0 applications ? Develop real-time web applications using ASP.NET Core ? Learn the differences between SOA and microservices and get started with microservice development using ASP.NET Core 2.0 ? Walk through functional programming with F# and .NET Core from scratch In Detail With the rise in the number of tools and technologies available today, developers and architects are always exploring ways to create better and smarter solutions. Before, the differences between target platforms was a major roadblock, but that's not the case now. .NET Core 2.0 By Example will take you on an exciting journey to building better software. This book provides fresh and relevant content to .NET Core 2.0 in a succinct format that’s enjoyable to read. It also delivers concepts, along with the implications, design decisions, and potential pitfalls you might face when targeting Linux and Windows systems, in a logical and simple way. With the .NET framework at its center, the book comprises of five varied projects: a multiplayer Tic-tac-toe game; a real-time chat application, Let'sChat; a chatbot; a microservice-based buying-selling application; and a movie booking application. You will start each chapter with a high-level overview of the content, followed by the above example applications described in detail. By the end of each chapter, you will not only be proficient with the concepts, but you’ll also have created a tangible component in the application. By the end of the book, you will have built five solid projects using all the tools and support provided by the .NET Core 2.0 framework. Style and approach This book takes a concise yet comprehensive project-based approach to teaching the tricks and tools of .NET Core 2.0.

Leverage this step-by-step guide to build a highly secure, fault-tolerant, and scalable Cloud environment About This Book ? Learn how to leverage various Amazon Web Services (AWS) components and services to build a secure, reliable, and robust environment to host your applications on. ? Delve into core AWS service offerings with hands-on tutorials, real-world use case scenarios, and best practices. ? A self-paced, systematic, and step-by-step guide to learning and implementing AWS in your own environment. Who This Book Is For This book is for those who want to learn and leverage the rich plethora of services provided by AWS. Although no prior experience with AWS is required, it is recommended that you have some hands-on experience of Linux, Web Services, and basic networking. What You Will Learn ? Take an in-depth look at what's new with AWS, along with how to effectively manage and automate your EC2 infrastructure with AWS Systems Manager ? Deploy and scale your applications with ease using AWS Elastic Beanstalk and Amazon Elastic File System ? Secure and govern your environments using AWS CloudTrail, AWS Config, and AWS Shield ? Learn the DevOps way using a combination of AWS CodeCommit, AWS CodeDeploy, and AWS CodePipeline ? Run big data analytics and workloads using Amazon EMR and Amazon Redshift ? Learn to back up and safeguard your data using AWS Data Pipeline ? Get started with the Internet of Things using AWS IoT and AWS Greengrass In Detail Many businesses are moving from traditional data centers to AWS because of its reliability, vast service offerings, lower costs, and high rate of innovation. AWS can be used to accomplish a variety of both simple and tedious tasks. Whether you are a seasoned system admin or a rookie, this book will help you to learn all the skills you need to work with the AWS cloud. This book guides you through some of the most popular AWS services, such as EC2, Elastic Beanstalk, EFS, CloudTrail, Redshift, EMR, Data Pipeline, and IoT using a simple, real-world, application-hosting example. This book will also enhance your application delivery skills with the latest AWS services, such as CodeCommit, CodeDeploy, and CodePipeline, to provide continuous delivery and deployment, while also securing and monitoring your environment's workflow. Each chapter is designed to provide you with maximal information about each AWS service, coupled with easy to follow, hands-on steps, best practices, tips, and recommendations. By the end of the book, you will be able to create a highly secure, fault-tolerant, and scalable environment for your applications to run on. Style and approach This in-depth and insightful guide is filled with easy-to-follow examples, real-world use cases, best practices, and recommendations that will help you design and leverage some of the most commonly used AWS services.

This book will teach the concepts of test driven development in Java so you can build clean, maintainable and robust code About This Book ? Explore the most popular TDD tools and frameworks and become more proficient in building applications ? Create applications with better code design, fewer bugs, and higher test coverage, enabling you to get them to market quickly ? Implement test-driven programming methods into your development workflows Who This Book Is For If you're an experienced Java developer and want to implement more effective methods of programming systems and applications, then this book is for you. What You Will Learn ? Explore the tools and frameworks required for effective TDD development ? Perform the Red-Green-Refactor process efficiently, the pillar around which all other TDD procedures are based ? Master effective unit testing in isolation from the rest of your code ? Design simple and easily maintainable code by implementing different techniques ? Use mocking frameworks and techniques to easily write and quickly execute tests ? Develop an application to implement behavior-driven development in conjunction with unit testing ? Enable and disable features using feature toggles In Detail Test-driven development (TDD) is a development approach that relies on a test-first procedure that emphasizes writing a test before writing the necessary code, and then refactoring the code to optimize it.The value of performing TDD with Java, one of the longest established programming languages, is to improve the productivity of programmers and the maintainability and performance of code, and develop a deeper understanding of the language and how to employ it effectively. Starting with the basics of TDD and understanding why its adoption is beneficial, this book will take you from the first steps of TDD with Java until you are confident enough to embrace the practice in your day-to-day routine.You'll be guided through setting up tools, frameworks, and the environment you need, and we will dive right into hands-on exercises with the goal of mastering one practice, tool, or framework at a time. You'll learn about the Red-Green-Refactor procedure, how to write unit tests, and how to use them as executable documentation.With this book, you'll also discover how to design simple and easily maintainable code, work with mocks, utilize behavior-driven development, refactor old legacy code, and release a half-finished feature to production with feature toggles.You will finish this book with a deep understanding of the test-driven development methodology and the confidence to apply it to application programming with Java. Style and approach An easy-to-follow, hands-on guide to building applications through effective coding practices. This book covers practical examples by introducing different problems, each one designed as a learning exercise to help you understand each aspect of TDD.

Manage state in Angular to write high performing web apps by combining the power of Flux, RxJS, and NgRx About This Book ? Learn what makes an excellent Angular application architecture ? Use Redux to write performant, consistent Angular applications ? Incorporate Reactive Programming principles and RxJS to make it easier to develop, test, and debug your Angular applications Who This Book Is For If you have been developing Angular applications and want to dive deeper into the Angular architecture with Redux, RxJS, and NgRx to write robust web apps, then this book is for you. What You Will Learn ? Understand the one-way data flow and Flux pattern ? Work with functional programming and asynchronous data streams ? Figure out how RxJS can help us address the flaws in promises ? Set up different versions of cascading calls ? Explore advanced operators ? Get familiar with the Redux pattern and its principles ? Test and debug different features of your application ? Build your own lightweight app using Flux, Redux, and NgRx In Detail Managing the state of large-scale web applications is a highly challenging task with the need to align different components, backends, and web workers harmoniously. When it comes to Angular, you can use NgRx, which combines the simplicity of Redux with the reactive programming power of RxJS to build your application architecture, making your code elegant and easy to reason about, debug, and test. In this book, we start by looking at the different ways of architecting Angular applications and some of the patterns that are involved in it. This will be followed by a discussion on one-way data flow, the Flux pattern, and the origin of Redux. The book introduces you to declarative programming or, more precisely, functional programming and talks about its advantages. We then move on to the reactive programming paradigm. Reactive programming is a concept heavily used in Angular and is at the core of NgRx. Later, we look at RxJS, as a library and master it. We thoroughly describe how Redux works and how to implement it from scratch. The two last chapters of the book cover everything NgRx has to offer in terms of core functionality and supporting libraries, including how to build a micro implementation of NgRx. This book will empower you to not only use Redux and NgRx to the fullest, but also feel confident in building your own version, should you need it. Style and approach This book covers everything there is to know to get well-acquainted with Angular without bogging you down. Everything is neatly laid out under clear headings for quick consultation, giving you the information required to understand a concept immediately.

Discover solutions to all your Tkinter and Python GUI development problems About This Book ? Integrate efficient Python GUI programming techniques with Tkinter ? Efficiently implement advanced MVC architectures in your Python GUI apps ? Solve all your problems related to Tkinter and Python GUI development Who This Book Is For This book is for Python developers who are familiar with the basics of the language syntax, data structures, and OOP. You do not need previous experience with Tkinter or other GUI development libraries. What You Will Learn ? Add widgets and handle user events ? Lay out widgets within windows using frames and the different geometry managers ? Configure widgets so that they have a customized appearance and behavior ? Improve the navigation of your apps with menus and dialogs ? Apply object-oriented programming techniques in Tkinter applications ? Use threads to achieve responsiveness and update the GUI ? Explore the capabilities of the canvas widget and the types of items that can be added to it ? Extend Tkinter applications with the TTK (themed Tkinter) module In Detail As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions. Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background. You will then make your apps leverage network resources effectively, perform 2D and 3D animation-related tasks, create 3D objects, and perform advanced graphical operations. Finally, this book covers using the canvas and themed widgets. By the end of the book, you will have an in-depth knowledge of Tkinter classes, and will know how to use them to build efficient and rich GUI applications. Style and approach A practical recipe-based guide that will help you find solutions to all your Tkinter and Python GUI development-related problems.

Use Python modules such as ArcPy, ArcREST and the ArcGIS API for Python to automate the analysis and mapping of geospatial data. About This Book ? Perform GIS analysis faster by automating tasks. ? Access the spatial data contained within shapefiles and geodatabases and transform between spatial reference systems. ? Automate the mapping of geospatial analyses and production of map books. Who This Book Is For If you are a GIS student or professional who needs an understanding of how to use ArcPy to reduce repetitive tasks and perform analysis faster, this book is for you. It is also a valuable book for Python programmers who want to understand how to automate geospatial analyses and implement ArcGIS Online data management. What You Will Learn ? Understand how to integrate Python into ArcGIS and make GIS analysis faster and easier. ? Create Python * using ArcGIS ModelBuilder. ? Learn to use ArcGIS online feature services and the basics of the ArcGIS REST API ? Understand the unique Python environment that is new with ArcGIS Pro ? Learn about the new ArcGIS Python API and how to use Anaconda and Jupyter with it ? Learn to control ArcGIS Enterprise using ArcPy In Detail ArcGIS allows for complex analyses of geographic information. The ArcPy module is used to * these ArcGIS analyses, providing a productive way to perform geo-analyses and automate map production. The second edition of the book focuses on new Python tools, such as the ArcGIS API for Python. Using Python, this book will guide you from basic Python *ing to advanced ArcPy * tools. This book starts off with setting up your Python environment for ArcGIS automation. Then you will learn how to output maps using ArcPy in MXD and update feature class in a geodatabase using arcpy and ArcGIS Online. Next, you will be introduced to ArcREST library followed by examples on querying, updating and manipulating ArcGIS Online feature services. Further, you will be enabling your *s in the browser and directly interacting with ArcGIS Online using Jupyter notebook. Finally, you can learn ways to use of ArcPy to control ArcGIS Enterprise and explore topics on deployments, data quality assurances, data updates, version control, and editing safeguards. By the end of the book, you will be equipped with the knowledge required to create automated analysis with administration reducing the time-consuming nature of GIS. Style and approach The book takes a pragmatic approach, showing ways to automate repetitive tasks and utilizing features of ArcPy with ArcGIS Pro and ArcGIS online.

Implement classic and functional data structures and algorithms using Python About This Book ? A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. ? Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. ? Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Who This Book Is For The book will appeal to Python developers. A basic knowledge of Python is expected. What You Will Learn ? Gain a solid understanding of Python data structures. ? Build sophisticated data applications. ? Understand the common programming patterns and algorithms used in Python data science. ? Write efficient robust code. In Detail Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. Style and approach The easy-to-read book with its fast-paced nature will improve the productivity of Python programmers and improve the performance of Python applications.

Deep dive into the unified, distributed storage system in order to provide excellent performance About This Book ? Leverage Ceph's advanced features such as erasure coding, tiering, and Bluestore ? Solve large-scale problems with Ceph as a tool by understanding its strengths and weaknesses to develop the best solutions ? A practical guide that covers engaging use cases to help you use advanced features of Ceph effectively Who This Book Is For If you are a developer and an administrator who has deployed a Ceph cluster before and are curious about some of the most advanced features in order to improve performance then this book is for you What You Will Learn ?Know when and how to use some of Ceph's advanced new features ? Set up a test cluster with Ansible and some virtual machines using VirtualBox and Vagrant ?Develop novel solutions to massive problems with librados and shared object classes. ? Choose intelligent parameters for an erasure coded pool and set it up. ? Configure the Bluestore settings and see how they interact with different hardware configurations. ? Keep Ceph running through thick and thin with tuning, monitoring and disaster recovery advice. In Detail Mastering Ceph covers all that you need to know to use Ceph effectively. Starting with design goals and planning steps that should be undertaken to ensure successful deployments, you will be guided through to setting up and deploying the Ceph cluster, with the help of orchestration tools. Key areas of Ceph including Bluestore, Erasure coding and cache tiering will be covered with help of examples. Development of applications which use Librados and Distributed computations with shared object classes are also covered. A section on tuning will take you through the process of optimisizing both Ceph and its supporting infrastructure. Finally, you will learn to troubleshoot issues and handle various scenarios where Ceph is likely not to recover on its own. By the end of the book, you will be able to successfully deploy and operate a resilient high performance Ceph cluster. Style and approach A practical guide which has each chapter explaining the concept, sharing tips and tricks and a use case to implement the most powerful features of Ceph

Take tiny steps to enter the big world of data science through this interesting guide About This Book ? Learn the fundamentals of machine learning and build your own intelligent applications ? Master the art of building your own machine learning systems with this example-based practical guide ? Work with important classification and regression algorithms and other machine learning techniques Who This Book Is For This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed. What You Will Learn ? Exploit the power of Python to handle data extraction, manipulation, and exploration techniques ? Use Python to visualize data spread across multiple dimensions and extract useful features ? Dive deep into the world of analytics to predict situations correctly ? Implement machine learning classification and regression algorithms from scratch in Python ? Be amazed to see the algorithms in action ? Evaluate the performance of a machine learning model and optimize it ? Solve interesting real-world problems using machine learning and Python as the journey unfolds In Detail Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. Style and approach This book is an enticing journey that starts from the very basics and gradually picks up pace as the story unfolds. Each concept is first succinctly defined in the larger context of things, followed by a detailed explanation of their application. Every concept is explained with the help of a project that solves a real-world problem, and involves hands-on work—giving you a deep insight into the world of machine learning. With simple yet rich language—Python—you will understand and be able to implement the examples with ease.

South African born Elon Musk is the renowned entrepreneur and innovator behind PayPal, SpaceX, Tesla, and SolarCity. Musk wants to save our planet; he wants to send citizens into space, to form a colony on Mars; he wants to make money while doing these things; and he wants us all to know about it. He is the real-life inspiration for the Iron Man series of films starring Robert Downey Junior. The personal tale of Musk’s life comes with all the trappings one associates with a great, drama-filled story. He was a freakishly bright kid who was bullied brutally at school, and abused by his father. In the midst of these rough conditions, and the violence of apartheid South Africa, Musk still thrived academically and attended the University of Pennsylvania, where he paid his own way through school by turning his house into a club and throwing massive parties. He started a pair of huge dot-com successes, including PayPal, which eBay acquired for $1.5 billion in 2002. Musk was forced out as CEO and so began his lost years in which he decided to go it alone and baffled friends by investing his fortune in rockets and electric cars. Meanwhile Musk’s marriage disintegrated as his technological obsessions took over his life ... Elon Musk is the Steve Jobs of the present and the future, and for the past twelve months, he has been shadowed by tech reporter, Ashlee Vance. Elon Musk: How the Billionaire CEO of Spacex and Tesla is Shaping our Future is an important, exciting and intelligent account of the real-life Iron Man.

Explore and use the agile techniques of SAP Activate Framework in your SAP Projects. About This Book ? Explore the three pillars of SAP Activate and see how it works in different scenario. ? Understand and Implement Agile and Scrum concepts in SAP Activate. ? Get to Grisp with SAP Activate framework and manage your SAP projects effectively. Who This Book Is For This book is for readers who want to understand the working of SAP Activate and use it to manage SAP projects. Prior knowledge of SAP Hana is must. What You Will Learn ? Understand the fundamentals of SAP S4/HANA. ? Get familiar with the structure and characteristics of SAP Activate. ? Explore the application scenarios of SAP Activate. ? Use Agile and Scrum in SAP Projects effectively and efficiently ? Implement your learning into a sample project to explore and understand the benefits of SAP Activate methodology. In Detail It has been a general observation that most SAP consultants and professionals are used to the conventional waterfall methodology. Traditionally, this method has been there for ages and we all grew up learning about it and started practicing it in real world. The evolution of agile methodology has revolutionized the way we manage our projects and businesses. SAP Activate is an innovative, next generation business suite that allows producing working deliverables straight away. Manage your SAP Project with SAP Activate, will take your learning to the next level. The book promises to make you understand and practice the SAP Activate Framework. The focus is to take you on a journey of all the phases of SAP Activate methodology and make you understand all the phases with real time project examples. The author explains how SAP Activate methodology can be used through real-world use cases, with a comprehensive discussion on Agile and Scrum, in the context of SAP Project. You will get familiar with SAP S4HANA which is an incredibly innovative platform for businesses which can store business data, interpret it, analyze it, process it in real time, and use it when it's needed depending upon the business requirement. Style and approach An easy to follow approach with concepts explained via scenarios and project examples

Use test-driven approach to develop highly-functional iOS apps with Swift 4 and Xcode 9 About This Book ? A practical guide to writing effective, organized, and clean code that works well ? Learn test-driven principles to help you build better-designed apps with fewer bugs ? A comprehensive overview of the techniques available for TDD in Swift Who This Book Is For To get the most out of this book, you will need some prior experience with Swift application development. You may have already heard about Test-Driven Development (TDD) but you don't need any prior experience of applying it to Swift applications. What You Will Learn ? Implement TDD in Swift application development ? Find bugs before you enter code using the TDD approach ? Use TDD to build models, view controllers, and views ? Test network code with asynchronous tests and stubs ? Write code that is a joy to read and maintain ? Develop functional tests to ensure the app works as planned In Detail Test-driven development (TDD) is a proven way to find software bugs early. Writing tests before you code improves the structure and maintainability of your apps. Using TDD, in combination with Swift 4's improved syntax, means there is no longer any excuse for writing bad code. This book will help you understand the process of TDD and how to apply it to your apps written in Swift. Through practical, real-world examples, you’ll learn how to implement TDD in context. You will begin with an overview of the TDD workflow and then delve into unit-testing concepts and code cycles. You will also plan and structure your test-driven iOS app, and write tests to drive the development of view controllers and helper classes. Next, you’ll learn how to write tests for network code and explore how the test-driven approach—in combination with stubs—helps you write network code even before the backend component is finished. Finally, the book will guide you through the next steps to becoming a testing expert by discussing integration tests, Behavior Driven Development (BDD), open source testing frameworks, and UI Tests (introduced in Xcode 9). Style and approach Using a step-by-step approach, you will develop an entire iOS app using TDD. During the course of the book, you will explore different strategies for writing tests for models, View Controllers, and networking code.

Learn, develop, and design applications using the new features in Microsoft Dynamics CRM About This Book ? Implement business logic using processes, plugins, and client-side *s with MS Dynamics 365 ? Develop custom CRM solutions to improve your business applications ? A comprehensive guide that covers the new features of Microsoft Dynamics 365 and increasingly advanced topics. Who This Book Is For This book targets skilled developers who are looking to build business-solution software and are new to application development in Microsoft Dynamics 365, especially for CRM. What You Will Learn ? Discover new designers tools included in Dynamics 365 CRM ? Develop apps using the platform-agnostic Web API ? Leverage Azure Extensions to design cloud-aware applications ? Learn how to implement CRUD operation ? Create integrated real-world apps using Microsoft PowerApps and Flow by combining services such as Twitter, Facebook, and SharePoint ? Configure and use Artificial Intelligence Azure Cognitive Services for Recommendation and Text Analytic services In Detail Microsoft Dynamics 365 CRM is the most trusted name in enterprise-level customer relationship management. Thelatest version of Dynamics CRM comes with the important addition of exciting features guaranteed to make your life easier. It comes straight off the shelf with a whole new frontier of updated business rules, process enhancements, SDK methods, and other enhancements. This book will introduce you to the components of the new designer tools, such as SiteMap, App Module, and Visual Designer for Business Processes. Going deeper, this book teaches you how to develop custom SaaS applications leveraging the features of PowerApps available in Dynamics 365.Further, you will learn how to automate business processes using Microsoft Flow, and then we explore Web API, the most important platform update in Dynamics 365 CRM. Here, you'll also learn how to implement Web API in custom applications. You will learn how to write an Azure-aware plugin to design and integrate cloud-aware solutions. The book concludes with configuring services using newly released features such as Editable grids, Data Export Service, LinkedIn Integration, Relationship Insights, and Live Assist. Style and approach The book takes a pragmatic approach, exploring Dynamics 365 and its CRM features with the help of real-world scenarios.

Enhance your organization’s secure posture by improving your attack and defense strategies About This Book ? Gain a clear understanding of the attack methods, and patterns to recognize abnormal behavior within your organization with Blue Team tactics. ? Learn to unique techniques to gather exploitation intelligence, identify risk and demonstrate impact with Red Team and Blue Team strategies. ? A practical guide that will give you hands-on experience to mitigate risks and prevent attackers from infiltrating your system. Who This Book Is For This book aims at IT professional who want to venture the IT security domain. IT pentester, Security consultants, and ethical hackers will also find this course useful. Prior knowledge of penetration testing would be beneficial. What You Will Learn ? Learn the importance of having a solid foundation for your security posture ? Understand the attack strategy using cyber security kill chain ? Learn how to enhance your defense strategy by improving your security policies, hardening your network, implementing active sensors, and leveraging threat intelligence ? Learn how to perform an incident investigation ? Get an in-depth understanding of the recovery process ? Understand continuous security monitoring and how to implement a vulnerability management strategy ? Learn how to perform log analysis to identify suspicious activities In Detail The book will start talking about the security posture before moving to Red Team tactics, where you will learn the basic syntax for the Windows and Linux tools that are commonly used to perform the necessary operations. You will also gain hands-on experience of using new Red Team techniques with powerful tools such as python and PowerShell, which will enable you to discover vulnerabilities in your system and how to exploit them. Moving on, you will learn how a system is usually compromised by adversaries, and how they hack user's identity, and the various tools used by the Red Team to find vulnerabilities in a system. In the next section, you will learn about the defense strategies followed by the Blue Team to enhance the overall security of a system. You will also learn about an in-depth strategy to ensure that there are security controls in each network layer, and how you can carry out the recovery process of a compromised system. Finally, you will learn how to create a vulnerability management strategy and the different techniques for manual log analysis. By the end of this book, you will be well-versed with Red Team and Blue Team techniques and will have learned the techniques used nowadays to attack and defend systems. Style and approach This book uses a practical approach of the cybersecurity kill chain to explain the different phases of the attack, which includes the rationale behind each phase, followed by scenarios and examples that brings the theory into practice.

Explore the concepts and tools you need to discover the world of microservices with various design patterns About This Book ? Get to grips with the microservice architecture and build enterprise-ready microservice applications ? Learn design patterns and the best practices while building a microservice application ? Obtain hands-on techniques and tools to create high-performing microservices resilient to possible fails Who This Book Is For This book is for architects and senior developers who would like implement microservice design patterns in their enterprise application development. The book assumes some prior programming knowledge. What You Will Learn ? How to break monolithic application into microservices ? Implement caching strategies, CQRS and event sourcing, and circuit breaker patterns ? Incorporate different microservice design patterns, such as shared data, aggregator, proxy, and chained ? Utilize consolidate testing patterns such as integration, signature, and monkey tests ? Secure microservices with JWT, API gateway, and single sign on ? Deploy microservices with continuous integration or delivery, Blue-Green deployment In Detail Microservices are a hot trend in the development world right now. Many enterprises have adopted this approach to achieve agility and the continuous delivery of applications to gain a competitive advantage. This book will take you through different design patterns at different stages of the microservice application development along with their best practices. Microservice Patterns and Best Practices starts with the learning of microservices key concepts and showing how to make the right choices while designing microservices. You will then move onto internal microservices application patterns, such as caching strategy, asynchronism, CQRS and event sourcing, circuit breaker, and bulkheads. As you progress, you'll learn the design patterns of microservices. The book will guide you on where to use the perfect design pattern at the application development stage and how to break monolithic application into microservices. You will also be taken through the best practices and patterns involved while testing, securing, and deploying your microservice application. At the end of the book, you will easily be able to create interoperable microservices, which are testable and prepared for optimum performance. Style and approach Comprehensive guide that uses architectural patterns with the best choices involved in application development

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

A practical guide designed to get you from basics to current state of art in computer vision systems. About This Book ? Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease ? Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more ? With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Who This Book Is For This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus. What You Will Learn ? Learn the basics of image manipulation with OpenCV ? Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more ? Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST ? Understand image transformation and downsampling with practical implementations. ? Explore neural networks for computer vision and convolutional neural networks using Keras ? Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more ? Explore deep-learning-based object tracking in action ? Understand Visual SLAM techniques such as ORB-SLAM In Detail In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. Style and approach Step-by-step guide filled with real-world, practical examples for understanding and applying various Computer Vision techniques

5 real-world projects to help you master deep learning concepts About This Book ? Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more ? Get to grips with R's impressive range of Deep Learning libraries and frameworks such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec ? Practical projects that show you how to implement different neural networks with helpful tips, tricks, and best practices Who This Book Is For Machine learning professionals and data scientists looking to master deep learning by implementing practical projects in R will find this book a useful resource. A knowledge of R programming and the basic concepts of deep learning is required to get the best out of this book. What You Will Learn ? Instrument Deep Learning models with packages such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec ? Apply neural networks to perform handwritten digit recognition using MXNet ? Get the knack of CNN models, Neural Network API, Keras, and TensorFlow for traffic sign classification ? Implement credit card fraud detection with Autoencoders ? Master reconstructing images using variational autoencoders ? Wade through sentiment analysis from movie reviews ? Run from past to future and vice versa with bidirectional Long Short-Term Memory (LSTM) networks ? Understand the applications of Autoencoder Neural Networks in clustering and dimensionality reduction In Detail R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. Deep Learning, as we all know, is one of the trending topics today, and is finding practical applications in a lot of domains. This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generation, and sentiment analysis. You'll learn how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks, and LSTMs—and apply them in practical scenarios. The book also highlights how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and techniques and how to use them in a practical setting. Style and approach This book's unique, learn-as-you-do approach ensures the reader builds on his understanding of deep learning progressively with each project. This book is designed in such a way that implementing each project will empower you with a unique skillset and enable you to implement the next project more confidently.