Power up your network applications with Python programming Key Features * Master Python skills to develop powerful network applications * Grasp the fundamentals and functionalities of SDN * Design multi-threaded, event-driven architectures for echo and chat servers Book Description This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You’ll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you’ll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming. By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products: * Practical Network Automation by Abhishek Ratan * Mastering Python Networking by Eric Chou * Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker What you will learn * Create socket-based networks with asynchronous models * Develop client apps for web APIs, including S3 Amazon and Twitter * Talk to email and remote network servers with different protocols * Integrate Python with Cisco, Juniper, and Arista eAPI for automation * Use Telnet and SSH connections for remote system monitoring * Interact with websites via XML-RPC, SOAP, and REST APIs * Build networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX * Configure virtual networks in different deployment environments Who this book is for If you are a Python developer or a system administrator who wants to start network programming, this Learning Path gets you a step closer to your goal. IT professionals and DevOps engineers who are new to managing network devices or those with minimal experience looking to expand their knowledge and skills in Python will also find this Learning Path useful. Although prior knowledge of networking is not required, some experience in Python programming will be helpful for a better understanding of the concepts in the Learning Path.

Perform advanced dashboard, visualization, and analytical techniques with Tableau Desktop, Tableau Prep, and Tableau Server Key Features * Unique problem-solution approach to aid effective business decision-making * Create interactive dashboards and implement powerful business intelligence solutions * Includes best practices on using Tableau with modern cloud analytics services Book Description Tableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ecosystem. This book is enriched with features such as Tableau extracts, Tableau advanced calculations, geospatial analysis, and building dashboards. It will guide you with exciting data manipulation, storytelling, advanced filtering, expert visualization, and forecasting techniques using real-world examples. From basic functionalities of Tableau to complex deployment on Linux, you will cover it all. Moreover, you will learn advanced features of Tableau using R, Python, and various APIs. You will learn how to prepare data for analysis using the latest Tableau Prep. In the concluding chapters, you will learn how Tableau fits the modern world of analytics and works with modern data platforms such as Snowflake and Redshift. In addition, you will learn about the best practices of integrating Tableau with ETL using Matillion ETL. By the end of the book, you will be ready to tackle business intelligence challenges using Tableau's features. What you will learn * Understand the basic and advanced skills of Tableau Desktop * Implement best practices of visualization, dashboard, and storytelling * Learn advanced analytics with the use of build in statistics * Deploy the multi-node server on Linux and Windows * Use Tableau with big data sources such as Hadoop, Athena, and Spectrum * Cover Tableau built-in functions for forecasting using R packages * Combine, shape, and clean data for analysis using Tableau Prep * Extend Tableau’s functionalities with REST API and R/Python Who this book is for Tableau 2019.x Cookbook is for data analysts, data engineers, BI developers, and users who are looking for quick solutions to common and not-so-common problems faced while using Tableau products. Put each recipe into practice by bringing the latest offerings of Tableau 2019.x to solve real-world analytics and business intelligence challenges. Some understanding of BI concepts and Tableau is required.

A comprehensive guide to get started with Java and gain insights into major concepts such as object-oriented, functional, and reactive programming Key Features * Strengthen your knowledge of important programming concepts and the latest features in Java * Explore core programming topics including GUI programming, concurrency, and error handling * Learn the idioms and best practices for writing high-quality Java code Book Description Java is one of the preferred languages among developers, used in everything right from smartphones, and game consoles to even supercomputers, and its new features simply add to the richness of the language. This book on Java programming begins by helping you learn how to install the Java Development Kit. You will then focus on understanding object-oriented programming (OOP), with exclusive insights into concepts like abstraction, encapsulation, inheritance, and polymorphism, which will help you when programming for real-world apps. Next, you’ll cover fundamental programming structures of Java such as data structures and algorithms that will serve as the building blocks for your apps. You will also delve into core programming topics that will assist you with error handling, debugging, and testing your apps. As you progress, you’ll move on to advanced topics such as Java libraries, database management, and network programming, which will hone your skills in building professional-grade apps. Further on, you’ll understand how to create a graphic user interface using JavaFX and learn to build scalable apps by taking advantage of reactive and functional programming. By the end of this book, you’ll not only be well versed with Java 10, 11, and 12, but also gain a perspective into the future of this language and software development in general. What you will learn * Learn and apply object-oriented principles * Gain insights into data structures and understand how they are used in Java * Explore multithreaded, asynchronous, functional, and reactive programming * Add a user-friendly graphic interface to your application * Find out what streams are and how they can help in data processing * Discover the importance of microservices and use them to make your apps robust and scalable * Explore Java design patterns and best practices to solve everyday problems * Learn techniques and idioms for writing high-quality Java code Who this book is for Students, software developers, or anyone looking to learn new skills or even a language will find this book useful. Although this book is for beginners, professional programmers can benefit from it too. Previous knowledge of Java or any programming language is not required.

Identify tools and techniques to secure and perform a penetration test on an AWS infrastructure using Kali Linux Key Features * Efficiently perform penetration testing techniques on your public cloud instances * Learn not only to cover loopholes but also to automate security monitoring and alerting within your cloud-based deployment pipelines * A step-by-step guide that will help you leverage the most widely used security platform to secure your AWS Cloud environment Book Description The cloud is taking over the IT industry. Any organization housing a large amount of data or a large infrastructure has started moving cloud-ward — and AWS rules the roost when it comes to cloud service providers, with its closest competitor having less than half of its market share. This highlights the importance of security on the cloud, especially on AWS. While a lot has been said (and written) about how cloud environments can be secured, performing external security assessments in the form of pentests on AWS is still seen as a dark art. This book aims to help pentesters as well as seasoned system administrators with a hands-on approach to pentesting the various cloud services provided by Amazon through AWS using Kali Linux. To make things easier for novice pentesters, the book focuses on building a practice lab and refining penetration testing with Kali Linux on the cloud. This is helpful not only for beginners but also for pentesters who want to set up a pentesting environment in their private cloud, using Kali Linux to perform a white-box assessment of their own cloud resources. Besides this, there is a lot of in-depth coverage of the large variety of AWS services that are often overlooked during a pentest — from serverless infrastructure to automated deployment pipelines. By the end of this book, you will be able to identify possible vulnerable areas efficiently and secure your AWS cloud environment. What you will learn * Familiarize yourself with and pentest the most common external-facing AWS services * Audit your own infrastructure and identify flaws, weaknesses, and loopholes * Demonstrate the process of lateral and vertical movement through a partially compromised AWS account * Maintain stealth and persistence within a compromised AWS account * Master a hands-on approach to pentesting * Discover a number of automated tools to ease the process of continuously assessing and improving the security stance of an AWS infrastructure Who this book is for If you are a security analyst or a penetration tester and are interested in exploiting Cloud environments to reveal vulnerable areas and secure them, then this book is for you. A basic understanding of penetration testing, cloud computing, and its security concepts is mandatory.

Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key Features * Explore advanced financial models used by the industry and ways of solving them using Python * Build state-of-the-art infrastructure for modeling, visualization, trading, and more * Empower your financial applications by applying machine learning and deep learning Book Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learn * Solve linear and nonlinear models representing various financial problems * Perform principal component analysis on the DOW index and its components * Analyze, predict, and forecast stationary and non-stationary time series processes * Create an event-driven backtesting tool and measure your strategies * Build a high-frequency algorithmic trading platform with Python * Replicate the CBOT VIX index with SPX options for studying VIX-based strategies * Perform regression-based and classification-based machine learning tasks for prediction * Use TensorFlow and Keras in deep learning neural network architecture Who this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.

A complete guide to understanding, developing, and testing popular security-token smart contracts Key Features * Understand key Blockchain and Ethereum platforms concepts * Step-by-step guide to developing STO smart contracts on Ethereum * Monetize digital tokens under various U.S. securities laws Book Description The failure of initial coin offerings (ICOs) is no accident, as most ICOs do not link to a real asset and are not regulated. Realizing the shortcomings of ICOs, the blockchain community and potential investors embraced security token offerings (STOs) and stablecoins enthusiastically. In this book, we start with an overview of the blockchain technology along with its basic concepts. We introduce the concept behind STO, and cover the basic requirements for launching a STO and the relevant regulations governing its issuance. We discuss U.S. securities laws development in launching security digital tokens using blockchain technology and show some real use cases. We also explore the process of STO launches and legal considerations. We introduce popular security tokens in the current blockchain space and talk about how to develop a security token DApp, including smart contract development for ERC1404 tokens. Later, you'll learn to build frontend side functionalities to interact with smart contracts. Finally, we discuss stablecoin technical design functionalities for issuing and operating STO tokens by interacting with Ethereum smart contracts. By the end of this book, you will have learned more about STOs and gained a detailed knowledge of building relevant applications—all with the help of practical examples. What you will learn * Understand the basic requirements for launching a security token offering * Explore various US securities laws governing the offering of security digital tokens * Get to grips with the stablecoin concept with the help of use cases * Learn how to develop security token decentralized applications * Understand the difference between ERC-20 and ERC-721 tokens * Learn how to set up a development environment and build security tokens * Explore the technical design of stablecoins Who this book is for This book is ideal for blockchain beginners and business user developers who want to quickly master popular Security Token Offerings and stablecoins. Readers will learn how to develop blockchain/digital cryptos, guided by U.S. securities laws and utilizing some real use cases. Prior exposure to an Object-Oriented Programming language such as JavaScript would be an advantage, but is not mandatory.

Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detection Key Features * Explore the latest features and APIs in OpenCV 4 and build computer vision algorithms * Develop effective, robust, and fail-safe vision for your applications * Build computer vision algorithms with machine learning capabilities Book Description OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work through recipes that implement a variety of tasks, such as facial recognition and detection. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by setting up OpenCV, and explains how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of the book, you'll be able to confidently implement a range to computer vision algorithms to meet the technical requirements of your complex CV projects What you will learn * Install and create a program using the OpenCV library * Segment images into homogenous regions and extract meaningful objects * Apply image filters to enhance image content * Exploit image geometry to relay different views of a pictured scene * Calibrate the camera from different image observations * Detect people and objects in images using machine learning techniques * Reconstruct a 3D scene from images * Explore face detection using deep learning Who this book is for If you’re a CV developer or professional who already uses or would like to use OpenCV for building computer vision software, this book is for you. You’ll also find this book useful if you’re a C++ programmer looking to extend your computer vision skillset by learning OpenCV.

A comprehensive guide to programming with network sockets, implementing Internet protocols, designing IoT devices, and much more with C Key Features * Leverage your C or C++ programming skills to build powerful network applications * Get to grips with a variety of network protocols that allow you to load web pages, send emails, and do much more * Write portable network code for operating systems such as Windows, Linux, and macOS Book Description Network programming, a challenging topic in C, is made easy to understand with a careful exposition of socket programming APIs. This book gets you started with modern network programming in C and the right use of relevant operating system APIs. This book covers core concepts, such as hostname resolution with DNS, that are crucial to the functioning of the modern web. You’ll delve into the fundamental network protocols, TCP and UDP. Essential techniques for networking paradigms such as client-server and peer-to-peer models are explained with the help of practical examples. You’ll also study HTTP and HTTPS (the protocols responsible for web pages) from both the client and server perspective. To keep up with current trends, you’ll apply the concepts covered in this book to gain insights into web programming for IoT. You’ll even get to grips with network monitoring and implementing security best practices. By the end of this book, you’ll have experience of working with client-server applications, and be able to implement new network programs in C. The code in this book is compatible with the older C99 version as well as the latest C18 and C++17 standards. Special consideration is given to writing robust, reliable, and secure code that is portable across operating systems, including Winsock sockets for Windows and POSIX sockets for Linux and macOS. What you will learn * Uncover cross-platform socket programming APIs * Implement techniques for supporting IPv4 and IPv6 * Understand how TCP and UDP connections work over IP * Discover how hostname resolution and DNS work * Interface with web APIs using HTTP and HTTPS * Acquire hands-on experience with Simple Mail Transfer Protocol (SMTP) * Apply network programming to the Internet of Things (IoT) Who this book is for If you're a developer or a system administrator who wants to enter the world of network programming, this book is for you. Basic knowledge of C programming is assumed.

Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features * Leverage Julia's high speed and efficiency to build fast, efficient applications * Perform supervised and unsupervised machine learning and time series analysis * Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: * Julia 1.0 Programming - Second Edition by Ivo Balbaert * Julia Programming Projects by Adrian Salceanu What you will learn * Create your own types to extend the built-in type system * Visualize your data in Julia with plotting packages * Explore the use of built-in macros for testing and debugging * Integrate Julia with other languages such as C, Python, and MATLAB * Analyze and manipulate datasets using Julia and DataFrames * Develop and run a web app using Julia and the HTTP package * Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features * Get introduced to Python's rich suite of libraries for statistical modeling * Implement regression, clustering and train neural networks from scratch * Includes real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn * Understand the importance of statistical modeling * Learn about the various Python packages for statistical analysis * Implement algorithms such as Naive Bayes, random forests, and more * Build predictive models from scratch using Python's scikit-learn library * Implement regression analysis and clustering * Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.

Design and implement professional-level programs by leveraging modern data structures and algorithms in Rust Key Features * Improve your productivity by writing more simple and easy code in Rust * Discover the functional and reactive implementations of traditional data structures * Delve into new domains of Rust, including WebAssembly, networking, and command-line tools Book Description Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: * Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta * Hands-On Data Structures and Algorithms with Rust by Claus Matzinger What you will learn * Design and implement complex data structures in Rust * Create and use well-tested and reusable components with Rust * Understand the basics of multithreaded programming and advanced algorithm design * Explore application profiling based on benchmarking and testing * Study and apply best practices and strategies in error handling * Create efficient web applications with the Actix-web framework * Use Diesel for type-safe database interactions in your web application Who this book is for If you are already familiar with an imperative language and now want to progress from being a beginner to an intermediate-level Rust programmer, this Learning Path is for you. Developers who are already familiar with Rust and want to delve deeper into the essential data structures and algorithms in Rust will also find this Learning Path useful.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.

Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Key Features * Learn how to select the most suitable Python library to solve your problem * Compare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use them * Delve into the applications of neural networks using real-world datasets Book Description Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The course begins by explaining how basic clustering works to find similar data points in a set. Once you are well versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. You will complete the course by challenging yourself through various interesting activities such as performing a Market Basket Analysis and identifying relationships between different merchandises. By the end of this course, you will have the skills you need to confidently build your own models using Python. What you will learn * Understand the basics and importance of clustering * Build k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packages * Explore dimensionality reduction and its applications * Use scikit-learn (sklearn) to implement and analyse principal component analysis (PCA)on the Iris dataset * Employ Keras to build autoencoder models for the CIFAR-10 dataset * Apply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction data Who this book is for This course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.

Delve into the world of Kotlin and learn to build powerful Android and web applications Key Features * Learn the fundamentals of Kotlin to write high-quality code * Test and debug your applications with the different unit testing frameworks in Kotlin * Explore Kotlin's interesting features such as null safety, reflection, and annotations Book Description Kotlin is a general-purpose programming language used for developing cross-platform applications. Complete with a comprehensive introduction and projects covering the full set of Kotlin programming features, this book will take you through the fundamentals of Kotlin and get you up to speed in no time. Learn Kotlin Programming covers the installation, tools, and how to write basic programs in Kotlin. You'll learn how to implement object-oriented programming in Kotlin and easily reuse your program or parts of it. The book explains DSL construction, serialization, null safety aspects, and type parameterization to help you build robust apps. You'll learn how to destructure expressions and write your own. You'll then get to grips with building scalable apps by exploring advanced topics such as testing, concurrency, microservices, coroutines, and Kotlin DSL builders. Furthermore, you'll be introduced to the kotlinx.serialization framework, which is used to persist objects in JSON, Protobuf, and other formats. By the end of this book, you'll be well versed with all the new features in Kotlin and will be able to build robust applications skillfully. What you will learn * Explore the latest Kotlin features in order to write structured and readable object-oriented code * Get to grips with using lambdas and higher-order functions * Write unit tests and integrate Kotlin with Java code * Create real-world apps in Kotlin in the microservices style * Use Kotlin extensions with the Java collections library * Uncover destructuring expressions and find out how to write your own * Understand how Java-nullable code can be integrated with Kotlin features Who this book is for If you’re a beginner or intermediate programmer who wants to learn Kotlin to build applications, this book is for you. You’ll also find this book useful if you’re a Java developer interested in switching to Kotlin.

Take your SAP ABAP skills to the next level by mastering ABAP programming techniques with the help of real-world examples Key Features * Become adept at building interfaces and explore ABAP tools and techniques * Discover the modern functionalities available in the latest version of ABAP * Learn the process of creating stunning HTML5 applications using SAPUI5 Book Description Advanced Business Application Programming (ABAP) is an established and complex programming language in the IT industry. This book is designed to help you use the latest ABAP techniques and apply legacy constructions using practical examples. You'll start with a quick refresher on language and database concepts, followed by agile techniques for adding custom code to a modern ABAP system. After this, you will get up to speed with the complete ABAP toolset for importing data to and from different environments. Next, you'll learn how to print forms and work with the different ABAP tools for Extensible Markup Language (XML) manipulation. While covering further chapters, you'll gain insights into building stunning UI5 interfaces, in addition to learning how to develop simple apps using the Business Object Processing Framework (BOPF). You will also pick up the technique of handling exceptions and performing testing in ABAP. In the concluding chapters, you can look forward to grasping various techniques for optimizing the performance of programs using a variety of performance analysis tools. By the end of this book, you will have the expertise you need to confidently build maintainable programs in Systems, Applications, and Products (SAP). What you will learn * Create stable and error-free ABAP programs * Leverage new ABAP concepts including object-oriented programming(OOP) and Model-View-Controller (MVC) * Learn to add custom code to your existing SAP program * Speed up your ABAP programs by spotting bottlenecks * Understand techniques such as performance tuning and optimization * Develop modern and beautiful user interfaces (UIs) in an ABAP environment * Build multiple classes with any nesting level Who this book is for This book is for developers who want to learn and use ABAP skills to become an industry expert. Familiarity with object-oriented programming concepts is expected.

Manage Microsoft Azure cloud services that span storage, security, networking, and compute cloud capabilities and ace the AZ-103 Exam Key Features * Master features and concepts pertaining to Azure's Administration services * Gain a deep understanding of various Azure services related to infrastructure, applications, and environments * Gauge yourself by giving mock tests with up-to-date exam questions Book Description Microsoft Azure Administrator – Exam Guide AZ-103 will cover all the exam objectives that will help you earn Microsoft Azure Administrator certification. Whether you want to clear AZ-103 exam or want hands-on experience in administering Azure, this study guide will help you achieve your objective. It covers the latest features and capabilities around configuring, managing, and securing Azure resources. Following Microsoft's AZ-103 exam syllabus, this guide is divided into five modules. The first module talks about how to manage Azure subscriptions and resources. You will be able to configure Azure subscription policies at Azure subscription level and learn how to use Azure policies for resource groups. Later, the book covers techniques related to implementing and managing storage in Azure. You will be able to create and configure backup policies and perform restore operations. The next module will guide you to create, configure, and deploy virtual machines for Windows and Linux. In the last two modules, you will learn about configuring and managing virtual networks and managing identities. The book concludes with effective mock tests along with answers so that you can confidently crack this exam. By the end of this book, you will acquire the skills needed to pass Exam AZ-103. What you will learn * Configure Azure subscription policies and manage resource groups * Monitor activity log by using Log Analytics * Modify and deploy Azure Resource Manager (ARM) templates * Protect your data with Azure Site Recovery * Learn how to manage identities in Azure * Monitor and troubleshoot virtual network connectivity * Manage Azure Active Directory Connect, password sync, and password writeback Who this book is for This book is for Azure administrators, systems administrators or anyone preparing for AZ 103 exam and wants to master Azure's various administration features. Readers should have proficiency in working with PowerShell, CLI and other day-to-day Azure administration tasks.

Build Prometheus ecosystems with metric-centric visualization, alerting, and querying Key Features * Integrate Prometheus with Alertmanager and Grafana for building a complete monitoring system * Explore PromQL, Prometheus' functional query language, with easy-to-follow examples * Learn how to deploy Prometheus components using Kubernetes and traditional instances Book Description Prometheus is an open source monitoring system. It provides a modern time series database, a robust query language, several metric visualization possibilities, and a reliable alerting solution for traditional and cloud-native infrastructure. This book covers the fundamental concepts of monitoring and explores Prometheus architecture, its data model, and how metric aggregation works. Multiple test environments are included to help explore different configuration scenarios, such as the use of various exporters and integrations. You’ll delve into PromQL, supported by several examples, and then apply that knowledge to alerting and recording rules, as well as how to test them. After that, alert routing with Alertmanager and creating visualizations with Grafana is thoroughly covered. In addition, this book covers several service discovery mechanisms and even provides an example of how to create your own. Finally, you’ll learn about Prometheus federation, cross-sharding aggregation, and also long-term storage with the help of Thanos. By the end of this book, you’ll be able to implement and scale Prometheus as a full monitoring system on-premises, in cloud environments, in standalone instances, or using container orchestration with Kubernetes. What you will learn * Grasp monitoring fundamentals and implement them using Prometheus * Discover how to extract metrics from common infrastructure services * Find out how to take full advantage of PromQL * Design a highly available, resilient, and scalable Prometheus stack * Explore the power of Kubernetes Prometheus Operator * Understand concepts such as federation and cross-shard aggregation * Unlock seamless global views and long-term retention in cloud-native apps with Thanos Who this book is for If you’re a software developer, cloud administrator, site reliability engineer, DevOps enthusiast or system admin looking to set up a fail-safe monitoring and alerting system for sustaining infrastructure security and performance, this book is for you. Basic networking and infrastructure monitoring knowledge will help you understand the concepts covered in this book.

Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features * A non data professionals guide to exploring Excel's financial functions and pivot tables * Learn to prepare various models for income and cash flow statements, and balance sheets * Learn to perform valuations and identify growth drivers with real-world case studies Book Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components of Excel for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn * Identify the growth drivers derived from processing historical data in Excel * Use discounted cash flow (DCF) for efficient investment analysis * Build a financial model by projecting balance sheets, profit, and loss * Apply a Monte Carlo simulation to derive key assumptions for your financial model * Prepare detailed asset and debt schedule models in Excel * Discover the latest and advanced features of Excel 2019 * Calculate profitability ratios using various profit parameters Who this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel.

A step-by-step guide to learning Flutter and Dart 2 for creating Android and iOS mobile applications Key Features * Get up to speed with the basics of Dart programming and delve into Flutter development * Understand native SDK and third-party libraries for building Android and iOS applications using Flutter * Package and deploy your Flutter apps to achieve native-like performance Book Description Google Flutter is a cross-platform mobile platform that makes it easier to write secure and high-performance native apps for iOS and Android. This book begins by introducing you to the Flutter framework and basics of Dart. You’ll learn to set up the development environment to get started with your Flutter project. The book will guide you through designing the user interface and user input functions for your app. As you progress, you’ll explore the navigator widget to manage your app routes and understand how to add transitions between screens. You’ll then get to grips with developing your own plugin and discover how to structure good plugin code. The book will help you display a map from the Flutter app, add markers and interactions to it, and use the Google Places API. You’ll build on your knowledge by not only adding tests to create a bug-free app, but also preparing it for deployment on Apple's App Store and Google Play. In later chapters, you’ll learn to improve the user experience with advanced features such as map integrations, platform-specific code with native programming languages, and personalized animation options for designing intuitive UIs. By the end of this book, you’ll be well-versed with Dart programming and have the skills to develop your own mobile apps or build a career as a Dart and Flutter app developer. What you will learn * Understand the fundamentals of the Dart programming language * Explore the core concepts of the Flutter UI and how it compiles for multiple platforms * Develop Flutter plugins and widgets and understand how to structure good plugin code * Style your apps with widgets and learn the difference between stateful and stateless widgets * Add animation to your UI using Flutter's AnimatedBuilder component * Integrate your native code into your Flutter codebase for native app performance Who this book is for This book is for developers looking to learn Google's revolutionary framework, Flutter from scratch. No knowledge of Flutter or Dart is required. However, basic programming language knowledge will be helpful.

Build your own cloud based Database as a Service using OpenStack Trove About This Book Familiarize yourself with the concept of Database as a Service and make your existing system scalable and efficient with OpenStack Trove Minimize the administrative tasks and complexities of managing your cloud infrastructure This is a fast-paced guide to datastore management on the OpenStack platform using OpenStack Trove Who This Book Is For If you are a DBA / system administrator / architect, or a student who wants to build a Database as a Service based on OpenStack, this book is for you. You should have a basic knowledge of OpenStack components, RDBMS/NoSQL, IaaS, and cloud computing. What You Will Learn Get to grips with the basics of OpenStack and the prerequisites to install Trove Understand the expectations of DBaaS and how Trove can help you achieve them Set up a basic installation of DevStack (Development Stack) in a virtual box Install Trove and utilize its configuration groups to manage and tune databases Use Image builder to create guest images for Trove Utilize Trove to provision your first database instance Back up and restore your databases with the help of Trove In Detail OpenStack has become an extremely popular solution to build public and private clouds with. Database as a Service (DBaaS) enables the delivery of more agile database services at lower costs. Some other benefits of DBaaS are secure database deployments and compliance to standards and best practices. Trove is a DBaaS built on OpenStack and is becoming more popular by the day. Since Trove is one of the most recent projects of OpenStack, DBAs and system administrators can find it difficult to set up and run a DBaaS using OpenStack Trove. This book helps DBAs make that step. We start by introducing you to the concepts of DBaaS and how is it implemented using OpenStack Trove. Following this, we look at implementing OpenStack and deploying Trove. Moving on, you will learn to create guest images to be used with Trove. We then look at how to provision databases in self-service mode, and how to perform administration tasks such as backup and recovery, and fine-tuning databases. At the end of the book, we will examine some advanced features of Trove such as replication. Style and approach This fast-paced, step-by-step guide introduces you to DBaaS, OpenStack Trove, and its components, leading you through building your own Cloud-based DBaaS. Using the DevStack deployment method, you will spend less time on installing OpenStack so you can devote more time to learning how to provision and manage databases in a DBaaS environment.

Discover how to build iOS and watchOS applications in Swift 2 using XcodeAbout This BookGets you up and running with Swift programming without any prior iOS development experience.A fast paced guide showing best practices and lets you get up to speed with Swift to quickly build your own iOS applicationsA unique practical approach to make your life with Swift easy.Who This Book Is ForAre you interested in learning SwiftDo you want to write iOS applications in SwiftIf yes, then this is the book for you. No prior iOS programming experience is assumed; however, having some experience with any programming language will be beneficial.What You Will LearnDive into Swift and explore its innovative and powerful syntaxWork with Swift in Xcode to get a unique and productive approach to developmentFind out how to create complete iOS applicationsDiscover rapid prototyping with a Swift playgroundGet to know how to use the Swift storyboard to develop multi-page applicationsGet to grips with parsing JSON and XML data from network sourcesBuild a network client for GitHub repositories, with full source code on GitHubIn DetailSwift was considered one of the biggest innovations last year, and certainly with Swift 2 announced at WWDC in 2015, this segment of the developer space will continue to be hot and dominating.This is a fast-paced guide to provide an overview of Swift programming and then walks you through in detail how to write iOS applications. Progress through chapters on custom views, networking, parsing and build a complete application as a Git repository, all by using Swift as the core languageStyle and approachThis fast-paced practical guide will quickly give you hands-on experience with all the features of Swift programming. Following the practical examples in the book will help you successfully create your own iOS applications.