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.

Enhance your programming skills by learning the intricacies of object oriented programming in C# 8 Key Features * Understand the four pillars of OOP; encapsulation, inheritance, abstraction and polymorphism * Leverage the latest features of C# 8 including nullable reference types and Async Streams * Explore various design patterns, principles, and best practices in OOP Book Description Object-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic. With the latest release of C#, you can look forward to new additions that improve object-oriented programming. This book will get you up to speed with OOP in C# in an engaging and interactive way. The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs. You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications. You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics. Next, you will learn the secrets of writing good code by following design patterns and design principles. You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET. Further on, you'll discover a chapter dedicated to the Git version control system. As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them. By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level. What you will learn * Master OOP paradigm fundamentals * Explore various types of exceptions * Utilize C# language constructs efficiently * Solve complex design problems by understanding OOP * Understand how to work with databases using ADO.NET * Understand the power of generics in C# * Get insights into the popular version control system, Git * Learn how to model and design your software Who this book is for This book is designed for people who are new to object-oriented programming. Basic C# skills are assumed, however, prior knowledge of OOP in any other language is not required.

A hands on approach to learning ReasonML from the perspective of a web developer. Key Features * Hands on learning by building a real world app shell that includes client-side routing and more. * Understand Reason’s ecosystem including BuckleScript and various npm workflows. * Learn how Reason differs from TypeScript and Flow, and how to use it to make refactoring less stressful. Book Description ReasonML, also known as Reason, is a new syntax and toolchain for OCaml that was created by Facebook and is meant to be approachable for web developers. Although OCaml has several resources, most of them are from the perspective of systems development. This book, alternatively, explores Reason from the perspective of web development. You'll learn how to use Reason to build safer, simpler React applications and why you would want to do so. Reason supports immutability by default, which works quite well in the context of React. In learning Reason, you will also learn about its ecosystem – BuckleScript, JavaScript interoperability, and various npm workflows. We learn by building a real-world app shell, including a client-side router with page transitions, that we can customize for any Reason project. You'll learn how to leverage OCaml's excellent type system to enforce guarantees about business logic, as well as preventing runtime type errors.You'll also see how the type system can help offload concerns that we once had to keep in our heads. We'll explore using CSS-in-Reason, how to use external JSON in Reason, and how to unit-test critical business logic. By the end of the book, you'll understand why Reason is exploding in popularity and will have a solid foundation on which to continue your journey with Reason. What you will learn * Learn why Reason is exploding in popularity and why it's the future of React * Become familiar with Reason's syntax and semantics * Learn about Reason's ecosystem: BuckleScript and JavaScript interoperability * Learn how to build React applications with Reason * Learn how to use Reason's type system as a tool to provide amazing guarantees * Gain a solid foundation on which to continue your journey Who this book is for The target audience of this book is web developers who are somewhat familiar with ReactJS and who want to learn why ReasonML is the future of ReactJS.

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.

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.

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.

Master the art of implementing scalable and reactive microservices in your production environment with Java 11 Key Features * Use domain-driven designs to build microservices * Explore various microservices design patterns such as service discovery, registration, and API Gateway * Use Kafka, Avro, and Spring Streams to implement event-based microservices Book Description Microservices are key to designing scalable, easy-to-maintain applications. This latest edition of Mastering Microservices with Java, works on Java 11. It covers a wide range of exciting new developments in the world of microservices, including microservices patterns, interprocess communication with gRPC, and service orchestration. This book will help you understand how to implement microservice-based systems from scratch. You'll start off by understanding the core concepts and framework, before focusing on the high-level design of large software projects. You'll then use Spring Security to secure microservices and test them effectively using REST Java clients and other tools. You will also gain experience of using the Netflix OSS suite, comprising the API Gateway, service discovery and registration, and Circuit Breaker. Additionally, you'll be introduced to the best patterns, practices, and common principles of microservice design that will help you to understand how to troubleshoot and debug the issues faced during development. By the end of this book, you'll have learned how to build smaller, lighter, and faster services that can be implemented easily in a production environment. What you will learn * Use domain-driven designs to develop and implement microservices * Understand how to implement microservices using Spring Boot * Explore service orchestration and distributed transactions using the Sagas * Discover interprocess communication using REpresentational State Transfer (REST) and events * Gain knowledge of how to implement and design reactive microservices * Deploy and test various microservices Who this book is for This book is designed for Java developers who are familiar with microservices architecture and now want to effectively implement microservices at an enterprise level. Basic knowledge and understanding of core microservice elements and applications is necessary.

Mivel az informatika egyre inkább átsz?vi életünket, a szoftverek min?ségével kapcsolatos elvárások egyre magasabbak. Egy szoftver el?állítása azonban nem csak programozásból áll, és a programozóktól sem lehet elvárni emberfeletti képességeket, a megrendel? el nem mondott elképzelésének t?kéletesen megfelel?, teljesen hibamentes munkát, mivel csak az nem hibázik, aki nem is dolgozik. Az informatika világában a szoftvertesztel?k azok, akik a szoftverek min?ségéért dolgoznak. A szoftvertesztel?k?n óriási felel?sség nyugszik és folyamatosan elvárások kereszttüzében kell helytállniuk. Mégis, szoftvertesztelés nélkül a legt?bb szoftver el sem jutna a felhasználókig, vagy ha igen, akkor megjelenésük botrányokkal, valamint óriási anyagi és erk?lcsi veszteségekkel járna együtt, a rengeteg fel nem tárt programhiba miatt. Szoftvertesztelésre és tesztel?kre ezért mindenképp szükség van. K?nyvünk a professzionális szoftvertesztelés alapjaival ismerteti meg az olvasót, számos gyakorlati példával f?szerezve, mell?zve a száraz, pusztán technikai megk?zelítés? leírásokat, kezdve a szoftvertesztelés általános bemutatásától, a fogalmak ismertetését?l, majd részleteiben tárgyalva a szoftvertesztelést és annak helyét a fejlesztési folyamatokban. Segítségével jó adag gyakorlati ismerettel vértezhetjük fel magunkat, melynek során valódi, a tesztelést támogató alkalmazásokat ismerhetünk meg, biztos alapot nyújtva a szoftvertesztelésben elhelyezked? leend? és gyakorló szakembereknek a mindennapi munkájukhoz. A szoftverteszteléssel most ismerked? szakembereknek és laikusoknak kimondottan hasznos lehet ez a k?nyv, de fejleszt?k és cégvezet?k számára is tartogat hasznos információkat, melyek segítségével bevezethetik, illetve hatékonyabbá tehetik a szoftvertesztelést munkájuk során.

Ha kíváncsi az olyan témákra, mint például hogy miként lehet felt?rni egy jelszót, vagy egy webhelyet, esetleg hogyan lehet lehallgatni bárki kommunikációját egy nyílt wifi hálózaton, akkor ez a k?nyv ?nnek szól. Sokan azt hiszik, hogy ezek ?rd?ng?s dolgok, pedig egyáltalán nem azok. ?ppen ezért fontos, hogy védekezni is kell ellenük, ami szintén nem bonyolult, csak egy kis odafigyelésre van szükség. K?nyvünk mindkét oldalt megmutatja, elrettentésképpen a lehet?ségeket, okulásként a védekezési módokat. Ha ?n azt hiszi, hogy biztonságban van, hiszen nem csinál semmi illegálisat és még vírusirtó is van a gépén, akkor nagyon téved! Teljesk?r? védelem ugyanis nem létezik! Ha elolvassa ezt a k?nyvet, meg fog d?bbenni, hogy milyen sok támadási lehet?ség van adataink ellen. A k?nyv, azon túl, hogy ismerteti, mit jelentenek az információbiztonsági szakkifejezések olyan témákkal foglalkozik, mint hogy milyen eszk?z?k támadhatók és hogyan, hogyan dolgozik egy hacker, mekkora kockázatot jelent az emberi tényez? (social engineering), stb. Kitér a jelszavak biztonságára, a kül?nféle hackeléshez használható programok és azok kezelésére, a billenty?zetnaplózási lehet?ségekre, a hálózatok és weboldalak támadására és felt?résére, az online bankolási kockázatokra, a titkosítási módszerekre, illetve hogy mit érdemes tenni a biztonságos adattárolás érdekében.Természetesen senkit sem akarunk illegális tevékenységre buzdítani, célunk sokkal inkább azt megmutatni, hogy mekkora veszélynek vagyunk kitéve, ezáltal a támadási és védekezési lehet?ségek bemutatásával ?szt?n?zzük az embereket a biztonságosabb számítógéphasználatra.

Dive and explore into the latest addons of the latest Git.About This Book·Master all the basic concepts of Git to protect your code and make it easier to evolve·Use Git proficiently, and learn how to resolve day-by-day challenges easily·This step-by-step guide is packed with examples to help you learn and work with Git's internalsWho This Book Is ForIf you are a software developer with little or no experience of versioning systems, or you are familiar with other centralized versioning systems, then this book is for you.If you have experience in server and system management and need to broaden your use of Git from a DevOps perspective, this book contains everything you need.What You Will Learn·Master Git fundamentals·Be able to "visualize," even with the help of a valid GUI tool·Write principal commands in a shell·Figure out the right strategy to run change your daily work with few or no annoyances·Explore the tools used to migrate to Git from the Subversion versioning system without losing your development history·Plan new projects and repositories with ease, using online services, or local network resourcesIn DetailSince its inception, Git has attracted skilled developers due to its robust, powerful, and reliable features. Its incredibly fast branching ability transformed a piece of code from a niche tool for Linux Kernel developers into a mainstream distributed versioning system. Like most powerful tools, Git can be hard to approach since it has a lot of commands, subcommands, and options that easily confuse newcomers.The 2nd edition of this very successful book will help you overcome this fear and become adept in all the basic tasks in Git. Building upon the success of the first book, we start with a brief step-by-step installation guide; after this, you'll delve into the essentials of Git. For those of you who have bought the first edition, this time we go into internals in far greater depth, talking less about theory and using much more practical examples.The book serves as a primer for topics to follow, such as branching and merging, creating and managing a GitHub personal repository, and fork and pull requests. You'll then learn the art of cherry-picking, taking only the commits you want, followed by Git blame. Finally, we'll see how to interoperate with a Subversion server, covering the concepts and commands needed to convert an SVN repository into a Git repository.To conclude, this is a collection of resources, links, and appendices to satisfy even the most curious.Style and approachThis short guide will help you understand the concepts and fundamentals of GIT is a step-by-step manner.

Learn how to run new and old Windows applications in Docker containers. About This Book ? Package traditional .NET Frameworks apps and new .NET Core apps as Docker images, and run them in containers for increased efficiency, portability, and security ? Design and implement distributed applications that run across connected containers, using enterprise-grade open source software from public Docker images ? Build a full Continuous Deployment pipeline for a .NET Framework application, and deploy it to a highly-available Docker swarm running in the cloud Who This Book Is For If you want to modernize an old monolithic application without rewriting it, smooth the deployment to production, or move to DevOps or the cloud, then Docker is the enabler for you. This book gives you a solid grounding in Docker so you can confidently approach all of these scenarios. What You Will Learn ? Comprehend key Docker concepts: images, containers, registries, and swarms ? Run Docker on Windows 10, Windows Server 2016, and in the cloud ? Deploy and monitor distributed solutions across multiple Docker containers ? Run containers with high availability and fail-over with Docker Swarm ? Master security in-depth with the Docker platform, making your apps more secure ? Build a Continuous Deployment pipeline by running Jenkins in Docker ? Debug applications running in Docker containers using Visual Studio ? Plan the adoption of Docker in your own organization In Detail Docker is a platform for running server applications in lightweight units called containers. You can run Docker on Windows Server 2016 and Windows 10, and run your existing apps in containers to get significant improvements in efficiency, security, and portability. This book teaches you all you need to know about Docker on Windows, from 101 to deploying highly-available workloads in production. This book takes you on a Docker journey, starting with the key concepts and simple examples of how to run .NET Framework and .NET Core apps in Windows Docker containers. Then it moves on to more complex examples—using Docker to modernize the architecture and development of traditional ASP.NET and SQL Server apps. The examples show you how to break up monoliths into distributed apps and deploy them to a clustered environment in the cloud, using the exact same artifacts you use to run them locally. To help you move confidently to production, it then explains Docker security, and the management and support options. The book finishes with guidance on getting started with Docker in your own projects, together with some real-world case studies for Docker implementations, from small-scale on-premises apps to very large-scale apps running on Azure. Style and approach Using a step-by-step approach, this book shows you how to use Docker on Windows. It includes practical examples and real-world technical and business scenarios that will help you effectively implement Docker in your environment.There are over 50 examples of Dockerized applications, using C# .NET projects as the source and packaging them into Docker images.

An easy to digest practical guide to Metasploit covering all aspects of the framework from installation, configuration, and vulnerability hunting to advanced client side attacks and anti-forensics. About This Book ? Carry out penetration testing in highly-secured environments with Metasploit ? Learn to bypass different defenses to gain access into different systems. ? A step-by-step guide that will quickly enhance your penetration testing skills. Who This Book Is For If you are a penetration tester, ethical hacker, or security consultant who wants to quickly learn the Metasploit framework to carry out elementary penetration testing in highly secured environments then, this book is for you. What You Will Learn ? Get to know the absolute basics of the Metasploit framework so you have a strong foundation for advanced attacks ? Integrate and use various supporting tools to make Metasploit even more powerful and precise ? Set up the Metasploit environment along with your own virtual testing lab ? Use Metasploit for information gathering and enumeration before planning the blueprint for the attack on the target system ? Get your hands dirty by firing up Metasploit in your own virtual lab and hunt down real vulnerabilities ? Discover the clever features of the Metasploit framework for launching sophisticated and deceptive client-side attacks that bypass the perimeter security ? Leverage Metasploit capabilities to perform Web application security scanning In Detail This book will begin by introducing you to Metasploit and its functionality. Next, you will learn how to set up and configure Metasploit on various platforms to create a virtual test environment. You will also get your hands on various tools and components used by Metasploit. Further on in the book, you will learn how to find weaknesses in the target system and hunt for vulnerabilities using Metasploit and its supporting tools. Next, you'll get hands-on experience carrying out client-side attacks. Moving on, you'll learn about web application security scanning and bypassing anti-virus and clearing traces on the target system post compromise. This book will also keep you updated with the latest security techniques and methods that can be directly applied to scan, test, hack, and secure networks and systems with Metasploit. By the end of this book, you'll get the hang of bypassing different defenses, after which you'll learn how hackers use the network to gain access into different systems. Style and approach This tutorial is packed with step-by-step instructions that are useful for those getting started with Metasploit. This is an easy-to-read guide to learning Metasploit from scratch that explains simply and clearly all you need to know to use this essential IT power tool.

Build cloud native applications in Python About This Book ? This is the only reliable resource that showcases the tools and techniques you need build robust and resilient cloud native applications in Python ? Learn how to architect your application on both, the AWS and Azure clouds for high availability ? Assess, monitor, and troubleshoot your applications in the cloud Who This Book Is For This book is ideal for developers with a basic knowledge of Python who want to learn to build, test, and scale their Python-based applications. No prior experience of writing microservices in Python is required. What You Will Learn ? Get to know “the way of the cloud”, including why developing good cloud software is fundamentally about mindset and discipline ? Know what microservices are and how to design them ? Create reactive applications in the cloud with third-party messaging providers ? Build massive-scale, user-friendly GUIs with React and Flux ? Secure cloud-based web applications: the do’s, don’ts, and options ? Plan cloud apps that support continuous delivery and deployment In Detail Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform Style and approach Filled with examples, this book takes a step-by-step approach to teach you each and every configuration you need to make your application highly available and fault tolerant.

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book ? Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. ? Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. ? Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn ? Acquaint yourself with important elements of Machine Learning ? Understand the feature selection and feature engineering process ? Assess performance and error trade-offs for Linear Regression ? Build a data model and understand how it works by using different types of algorithm ? Learn to tune the parameters of Support Vector machines ? Implement clusters to a dataset ? Explore the concept of Natural Processing Language and Recommendation Systems ? Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.