Conquer complex and interesting programming challenges by building robust and concurrent applications with caches, cryptography, and parallel programming. Key Features * Understand how to use .NET frameworks like the Task Parallel Library (TPL)and CryptoAPI * Develop a containerized application based on microservices architecture * Gain insights into memory management techniques in .NET Core Book Description This Learning Path shows you how to create high performing applications and solve programming challenges using a wide range of C# features. You’ll begin by learning how to identify the bottlenecks in writing programs, highlight common performance pitfalls, and apply strategies to detect and resolve these issues early. You'll also study the importance of micro-services architecture for building fast applications and implementing resiliency and security in .NET Core. Then, you'll study the importance of defining and testing boundaries, abstracting away third-party code, and working with different types of test double, such as spies, mocks, and fakes. In addition to describing programming trade-offs, this Learning Path will also help you build a useful toolkit of techniques, including value caching, statistical analysis, and geometric algorithms. This Learning Path includes content from the following Packt products: * C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan * Practical Test-Driven Development using C# 7 by John Callaway, Clayton Hunt * The Modern C# Challenge by Rod Stephens What you will learn * Measure application performance using BenchmarkDotNet * Leverage the Task Parallel Library (TPL) and Parallel Language Integrated Query (PLINQ)library to perform asynchronous operations * Modify a legacy application to make it testable * Use LINQ and PLINQ to search directories for files matching patterns * Find areas of polygons using geometric operations * Randomize arrays and lists with extension methods * Use cryptographic techniques to encrypt and decrypt strings and files Who this book is for If you want to improve the speed of your code and optimize the performance of your applications, or are simply looking for a practical resource on test driven development, this is the ideal Learning Path for you. Some familiarity with C# and .NET will be beneficial.

Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features * Turn your designs into working software by learning the Python syntax * Write robust code with a solid understanding of Python data structures * Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: * Learn Python Programming - Second Edition by Fabrizio Romano * Python Data Structures and Algorithms by Benjamin Baka * Python 3 Object-Oriented Programming by Dusty Phillips What you will learn * Use data structures and control flow to write code * Use functions to bundle together a sequence of instructions * Implement objects in Python by creating classes and defining methods * Design public interfaces using abstraction, encapsulation and information hiding * Raise, define, and manipulate exceptions using special error objects * Create bulletproof and reliable software by writing unit tests * Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.

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

Create distributed applications with clever design patterns to solve complex problems Key Features * Set up and run distributed algorithms on a cluster using Dask and PySpark * Master skills to accurately implement concurrency in your code * Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: * Python High Performance - Second Edition by Gabriele Lanaro * Mastering Concurrency in Python by Quan Nguyen * Mastering Python Design Patterns by Sakis Kasampalis What you will learn * Use NumPy and pandas to import and manipulate datasets * Achieve native performance with Cython and Numba * Write asynchronous code using asyncio and RxPy * Design highly scalable programs with application scaffolding * Explore abstract methods to maintain data consistency * Clone objects using the prototype pattern * Use the adapter pattern to make incompatible interfaces compatible * Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features * Discover best practices for engineering and maintaining OpenCV projects * Explore important deep learning tools for image classification * Understand basic image matrix formats and filters Book Description OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: * Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá * Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendon?a, and Prateek Joshi What you will learn * Stay up-to-date with algorithmic design approaches for complex computer vision tasks * Work with OpenCV's most up-to-date API through various projects * Understand 3D scene reconstruction and Structure from Motion (SfM) * Study camera calibration and overlay augmented reality (AR) using the ArUco module * Create CMake scripts to compile your C++ application * Explore segmentation and feature extraction techniques * Remove backgrounds from static scenes to identify moving objects for surveillance * Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is for If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.

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

Use Unity 2017 to create fun and unbelievable AI entities in your games with A*, Fuzzy logic and NavMesh About This Book ? Explore the brand-new Unity 2017 features that makes implementing Artificial Intelligence in your game easier than ever ? Use fuzzy logic concepts in your AI decision-making to make your characters more engaging ? Build exciting and richer games by mastering advanced Artificial Intelligence concepts such as Neural Networks Who This Book Is For This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your first game or are looking to expand your knowledge as a game programmer, you will find plenty of exciting information and examples of game AI in terms of concepts and implementation. What You Will Learn ? Understand the basic terminology and concepts in game AI ? Explore advanced AI Concepts such as Neural Networks ? Implement a basic finite state machine using state machine behaviors in Unity 2017 ? Create sensory systems for your AI and couple it with a Finite State Machine ? Wok with Unity 2017's built-in NavMesh features in your game ? Build believable and highly-efficient artificial flocks and crowds ? Create a basic behavior tree to drive a character's actions In Detail Unity 2017 provides game and app developers with a variety of tools to implement Artificial Intelligence. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This third edition with Unity will help you break down Artificial Intelligence into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts, and features related to game AI in Unity 5. Further on you will learn to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You will then learn how to implement simple flocks and crowd's dynamics, key AI concepts. Moving on, you will learn how to implement a behavior tree through a game-focused example. Lastly, you'll combine fuzzy logic concepts with state machines and apply all the concepts in the book to build a simple tank game. Style and approach A self-explanatory practical guide with a series of tips and tricks on creating AI games with ease.

The Fourth Edition of the industry-acclaimed OpenStack Cloud Computing Cookbook, from four recognized experts, updated to the latest OpenStack build including Cinder, Nova, and Neutron. About This Book ? Over 100 recipes created by a team of OpenStack experts ? Updated to work with the latest OpenStack builds, with recipes covering the installation and use of OpenStack with Ansible ? It covers topics such as Keystone, Glance, Neutron, Nova, Cinder, and more, plus recipes for OpenStack storage, networking, and orchestrating workloads ? Test drive OpenStack using the accompanying Vagrant environment Who This Book Is For This book is written for cloud system engineers, system administrators, and technical architects who are moving from a virtualized environment to cloud environments. This book assumes that you are familiar with cloud computing platforms, and have knowledge of virtualization, networking, and managing Linux environments. What You Will Learn ? Understand, install, configure, and manage a complete OpenStack Cloud platform using OpenStack-Ansible ? Configure networks, routers, load balancers, and more with Neutron ? Use Keystone to setup domains, roles, groups and user access ? Learn how to use Swift and setup container access control lists ? Gain hands-on experience and familiarity with Horizon, the OpenStack Dashboard user interface ? Automate complete solutions with our recipes on Heat, the OpenStack Orchestration service as well as using Ansible to orchestrate application workloads ? Follow practical advice and examples to run OpenStack in production In Detail This is the fourth edition of the industry-acclaimed OpenStack Cloud Computing Cookbook, created by four recognized OpenStack experts. It has now been updated to work with the latest OpenStack builds, using tools and processes based on their collective and vast OpenStack experience. OpenStack Open Source Cloud software is one of the most used cloud infrastructures to support a wide variety of use cases, from software development to big data analysis. It is developed by a thriving community of individual developers from around the globe and backed by most of the leading players in the cloud space today. We make it simple to implement, massively scalable, and able to store a large pool of data and networking resources. OpenStack has a strong ecosystem that helps you provision your cloud storage needs. Add OpenStack's enterprise features to reduce the cost of your business. This book will begin by showing you the steps to build up an OpenStack private cloud environment using Ansible. You'll then discover the uses of cloud services such as the identity service, image service, and compute service. You'll dive into Neutron, the OpenStack Networking service, and get your hands dirty with configuring networks, routers, load balancers, and more. You’ll then gather more expert knowledge on OpenStack cloud computing by managing your cloud's security and migration. After that, we delve into OpenStack Object storage and you’ll see how to manage servers and work with objects, cluster, and storage functionalities. Finally, you will learn about OpenStack dashboard, Ansible, Keystone, and other interesting topics. Style and approach Clear, step-by-step instructions coupled with practical and applicable recipes that will enable you to use and implement the latest features of OpenStack. The authors provide all the context you need around each recipe so that you can make it part of your own OpenStack solutions.

Learn to confidently setup and create app, lenses, dashboards using Salesforce Einstein Analytics. About This Book ? Explore Einstein analytics on desktop as well as mobile platforms ? Turn data into smarter sales with Einstein Analytics for Sales ? Visualize your data with preloaded as well as customized dashboards Who This Book Is For This book is for data scientists, business users, developers who want to explore business data using the Salesforce Einstein Analytics. Knowledge of the Salesforce platform is required. What You Will Learn ? Create app, lenses, and dashboards using Einstein. ? Visualize data utilizing all the widgets available with Einstein. ? Understand Einstein for Sales, Service, and Marketing separately. ? Use Data monitoring tools to monitor data flow and system jobs. ? Abstract machine learning constructs and make predictions on events In Detail Salesforce Einstein analytics aka Wave Analytics is a cloud-based platform which connects data from the multiple sources and explores it to uncover insights. It empowers sales reps, marketers, and analysts with the insights to make customer interactions smarter, without building mathematical models. You will learn to create app, lenses, dashboards and share dashboards with other users. This book starts off with explaining you fundamental concepts like lenses, step, measures and sets you up with Einstein Analytics platform. We then move on to creating an app and here you will learn to create datasets, dashboards and different ways to import data into Analytics. Moving on we look at Einstein for sales, services, and marketing individually. Here you will learn to manage your pipeline, understand important business drivers and visualize trends. You will also learn features related to data monitoring tools and embedding dashboards with lightning, visualforce page and mobile devices. Further, you will learn advanced features pertaining to recent advancements in Einstein which include machine learning constructs and getting predictions for events. By the end of this book, you will become proficient in the Einstein analytics, getting insights faster and understanding your customer in a better way. Style and approach The book takes a pragmatic approach showing you installation of Salesforce Einstein Analytics, predictive analysis and applications of AI.

Maximize your administration skills effectively and efficiently About This Book ? Implement cost-effective virtualization solutions for your organization with actionable recipes ? Explore the concepts of VMM with real-world use cases ? Use the latest features with VMM 2016 such as Cluster OS Rolling Upgrade, Guarded Fabric and Storage Spaces Direct Who This Book Is For If you are a solutions architect, technical consultant, administrator, or any other virtualization enthusiast who needs to use Microsoft System Center Virtual Machine Manager in a real-world environment, then this is the book for you. What You Will Learn ? Plan and design a VMM architecture for real-world deployment ? Configure fabric resources, including compute, networking, and storage ? Create and manage Storage Spaces Direct clusters in VMM ? Configure Guarded Fabric with Shielded VMs ? Create and deploy virtual machine templates and multi-tier services ? Manage Hyper-V and VMware environments from VMM ? Enhance monitoring and management capabilities ? Upgrade to VMM 2016 from previous versions In Detail Virtual Machine Manager (VMM) 2016 is part of the System Center suite to configure and manage datacenters and offers a unified management experience on-premises and Azure cloud. This book will be your best companion for day-to-day virtualization needs within your organization, as it takes you through a series of recipes to simplify and plan a highly scalable and available virtual infrastructure. You will learn the deployment tips, techniques, and solutions designed to show users how to improve VMM 2016 in a real-world scenario. The chapters are divided in a way that will allow you to implement the VMM 2016 and additional solutions required to effectively manage and monitor your fabrics and clouds. We will cover the most important new features in VMM 2016 across networking, storage, and compute, including brand new Guarded Fabric, Shielded VMs and Storage Spaces Direct. The recipes in the book provide step-by-step instructions giving you the simplest way to dive into VMM fabric concepts, private cloud, and integration with external solutions such as VMware, Operations Manager, and the Windows Azure Pack. By the end of this book, you will be armed with the knowledge you require to start designing and implementing virtual infrastructures in VMM 2016. Style and approach This book follows a recipe-based approach similar to our previous two successful editions, covering the practical application of the major features in VMM 2016.

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.

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.

Evade antiviruses and bypass firewalls with the most widely used penetration testing frameworks Key Features * Gain insights into the latest antivirus evasion techniques * Set up a complete pentesting environment using Metasploit and virtual machines * Discover a variety of tools and techniques that can be used with Kali Linux Book Description Penetration testing or ethical hacking is a legal and foolproof way to identify vulnerabilities in your system. With thorough penetration testing, you can secure your system against the majority of threats. This Learning Path starts with an in-depth explanation of what hacking and penetration testing is. You’ll gain a deep understanding of classical SQL and command injection flaws, and discover ways to exploit these flaws to secure your system. You'll also learn how to create and customize payloads to evade antivirus software and bypass an organization's defenses. Whether it’s exploiting server vulnerabilities and attacking client systems, or compromising mobile phones and installing backdoors, this Learning Path will guide you through all this and more to improve your defense against online attacks. By the end of this Learning Path, you'll have the knowledge and skills you need to invade a system and identify all its vulnerabilities. This Learning Path includes content from the following Packt products: * Web Penetration Testing with Kali Linux - Third Edition by Juned Ahmed Ansari and Gilberto Najera-Gutierrez * Metasploit Penetration Testing Cookbook - Third Edition by Abhinav Singh , Monika Agarwal, et al What you will learn * Build and analyze Metasploit modules in Ruby * Integrate Metasploit with other penetration testing tools * Use server-side attacks to detect vulnerabilities in web servers and their applications * Explore automated attacks such as fuzzing web applications * Identify the difference between hacking a web application and network hacking * Deploy Metasploit with the Penetration Testing Execution Standard (PTES) * Use MSFvenom to generate payloads and backdoor files, and create shellcode Who this book is for This Learning Path is designed for security professionals, web programmers, and pentesters who want to learn vulnerability exploitation and make the most of the Metasploit framework. Some understanding of penetration testing and Metasploit is required, but basic system administration skills and the ability to read code are a must.

Explore distributed ledger technology, decentralization, and smart contracts and develop real-time decentralized applications with Ethereum and Solidity Key Features * Get to grips with the underlying technical principles and implementations of blockchain * Build powerful applications using Ethereum to secure transactions and create smart contracts * Gain advanced insights into cryptography and cryptocurrencies Book Description Blockchain technology is a distributed ledger with applications in industries such as finance, government, and media. This Learning Path is your guide to building blockchain networks using Ethereum, JavaScript, and Solidity. You will get started by understanding the technical foundations of blockchain technology, including distributed systems, cryptography and how this digital ledger keeps data secure. Further into the chapters, you’ll gain insights into developing applications using Ethereum and Hyperledger. As you build on your knowledge of Ether security, mining , smart contracts, and Solidity, you’ll learn how to create robust and secure applications that run exactly as programmed without being affected by fraud, censorship, or third-party interference. Toward the concluding chapters, you’ll explore how blockchain solutions can be implemented in applications such as IoT apps, in addition to its use in currencies. The Learning Path will also highlight how you can increase blockchain scalability and even discusses the future scope of this fascinating and powerful technology. By the end of this Learning Path, you'll be equipped with the skills you need to tackle pain points encountered in the blockchain life cycle and confidently design and deploy decentralized applications. This Learning Path includes content from the following Packt products: * Mastering Blockchain - Second Edition by Imran Bashir * Building Blockchain Projects by Narayan Prusty What you will learn * Understand why decentralized applications are important * Discover the mechanisms behind bitcoin and alternative cryptocurrencies * Master how cryptography is used to secure data with the help of examples * Maintain, monitor, and manage your blockchain solutions * Create Ethereum wallets * Explore research topics and the future scope of blockchain technology Who this book is for This Learning Path is designed for blockchain developers who want to build decentralized applications and smart contracts from scratch using Hyperledger. Basic familiarity with any programming language will be useful to get started with this Learning Path.

Leverage the full potential of IoT with the combination of Raspberry Pi 3 and Python and architect a complete IoT system that is the best fit for your organization Key Features * Build complex Python-based applications with IoT * Explore different concepts, technologies, and tradeoffs in the IoT architectural stack * Delve deep into each element of the IoT design—from sensors to the cloud Book Description The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. We’ll begin our journey with an introduction to Raspberry Pi and quickly jump right into Python programming. We’ll learn all concepts through multiple projects, and then reinforce our learnings by creating an IoT robot car. We’ll examine modern sensor systems and focus on what their power and functionality can bring to our system. We’ll also gain insight into cloud and fog architectures, including the OpenFog standards. The Learning Path will conclude by discussing three forms of prevalent attacks and ways to improve the security of our IoT infrastructure. By the end of this Learning Path, we will have traversed the entire spectrum of technologies needed to build a successful IoT system, and will have the confidence to build, secure, and monitor our IoT infrastructure. This Learning Path includes content from the following Packt products: * Internet of Things Programming Projects by Colin Dow * Internet of Things for Architects by Perry Lea What you will learn * Build a home security dashboard using an infrared motion detector * Receive data and display it with an actuator connected to the Raspberry Pi * Build an IoT robot car that is controlled via the Internet * Use IP-based communication to easily and quickly scale your system * Explore cloud protocols, such as Message Queue Telemetry Transport (MQTT) and CoAP * Secure communication with encryption forms, such as symmetric key Who this book is for This Learning Path is designed for developers, architects, and system designers who are interested in building exciting projects with Python by understanding the IoT ecosphere, various technologies, and tradeoffs. Technologists and technology managers who want to develop a broad view of IoT architecture, will also find this Learning Path useful. Prior programming knowledge of Python is a must.

Search, analyze, and manage data effectively with Elasticsearch 7 Key Features * Extend Elasticsearch functionalities and learn how to deploy on Elastic Cloud * Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies * Explore the capabilities of Elasticsearch 7 with easy-to-follow recipes Book Description Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics. Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch. What you will learn * Create an efficient architecture with Elasticsearch * Optimize search results by executing analytics aggregations * Build complex queries by managing indices and documents * Monitor the performance of your cluster and nodes * Design advanced mapping to take full control of index steps * Integrate Elasticsearch in Java, Scala, Python, and big data applications * Install Kibana to monitor clusters and extend it for plugins Who this book is for If you’re a software engineer, big data infrastructure engineer, or Elasticsearch developer, you'll find this book useful. This Elasticsearch book will also help data professionals working in the e-commerce and FMCG industry who use Elastic for metrics evaluation and search analytics to get deeper insights for better business decisions. Prior experience with Elasticsearch will help you get the most out of this book.

Get close and comfortable with Unity and build applications that run on HoloLens, Daydream, and Oculus Rift Key Features * Build fun augmented reality applications using ARKit, ARCore, and Vuforia * Explore virtual reality by developing more than 10 engaging projects * Learn how to integrate AR and VR concepts together in a single application Book Description Unity is the leading platform to develop mixed reality experiences because it provides a great pipeline for working with 3D assets. Using a practical and project-based approach, this Learning Path educates you about the specifics of AR and VR development using Unity 2018 and Unity 3D. You’ll learn to integrate, animate, and overlay 3D objects on your camera feed, before moving on to implement sensor-based AR applications. You’ll explore various concepts by creating an AR application using Vuforia for both macOS and Windows for Android and iOS devices. Next, you’ll learn how to develop VR applications that can be experienced with devices, such as Oculus and Vive. You’ll also explore various tools for VR development: gaze-based versus hand controller input, world space UI canvases, locomotion and teleportation, timeline animation, and multiplayer networking. You’ll learn the Unity 3D game engine via the interactive Unity Editor and C# programming. By the end of this Learning Path, you’ll be fully equipped to develop rich, interactive mixed reality experiences using Unity. This Learning Path includes content from the following Packt products: * Unity Virtual Reality Projects - Second Edition by Jonathan Linowes * Unity 2018 Augmented Reality Projects by Jesse Glover What you will learn * Create 3D scenes to learn about world space and scale * Move around your scenes using locomotion and teleportation * Create filters or overlays that work with facial recognition software * Interact with virtual objects using eye gaze, hand controllers, and user input events * Design and build a VR storytelling animation with a soundtrack and timelines * Create social VR experiences with Unity networking Who this book is for If you are a game developer familiar with 3D computer graphics and interested in building your own AR and VR games or applications, then this Learning Path is for you. Any prior experience in Unity and C# will be an advantage. In all, this course teaches you the tools and techniques to develop engaging mixed reality applications.

Explore the fundamentals of Dynamics 365 Business Central and the Visual Studio Code development environment with the help of useful examples and case studies Key Features * Tailor your applications to best suit the needs of your business * Explore the latest features of Business Central with examples curated by industry experts * Integrate Business Central features in your applications with this comprehensive guide Book Description Microsoft Dynamics 365 Business Central is a full ERP business solution suite with a robust set of development tools to support customization and enhancement. These tools can be used to tailor Business Central's in-built applications to support complete management functions for finance, supply chain, manufacturing, and operations. Using a case study approach, this book will introduce you to Dynamics 365 Business Central and Visual Studio Code development tools to help you become a productive Business Central developer. You'll also learn how to evaluate a product's development capabilities and manage Business Central-based development and implementation. You'll explore application structure, the construction of and uses for each object type, and how it all fits together to build apps that meet special business requirements. By the end of this book, you'll understand how to design and develop high-quality software using the Visual Studio Code development environment, the AL language paired with the improved editor, patterns, and features. What you will learn * Programming using the AL language in the Visual Studio Code development environment * Explore functional design and development using AL * How to build interactive pages and learn how to extract data for users * How to use best practices to design and develop modifications for new functionality integrated with the standard Business Central software * Become familiar with deploying the broad range of components available in a Business Central system * Create robust, viable systems to address specific business requirements Who this book is for If you want to learn about Dynamics 365 Business Central's powerful and extensive built-in development capabilities, this is the book for you. ERP consultants and managers of Business Central development will also find this book helpful. Although you aren't expected to have worked with Dynamics Business Central, basic understanding of programming and familiarity with business application software will help you understand the concepts covered in this book.

Over 70 recipes to effectively apply DevOps best practices and implement Agile, Git, CI-CD & Test automation using Azure DevOps Server (TFS) 2019 Key Features * Learn improving code quality using pull requests, branch policies, githooks and git branching design * Accelerate the deployment of high quality software by automating build and releases using CI-CD Pipelines. * Learn tried and tested techniques to automate database deployments, App Service & Function Deployments in Azure. Book Description Azure DevOps Server, previously known as Team Foundation Server (TFS), is a comprehensive on-premise DevOps toolset with a rich ecosystem of open source plugins. This book is your one stop guide to learn how to effectively use all of these Azure DevOps services to go from zero to DevOps. You will start by building high-quality scalable software targeting .NET, .NET core or Node.js applications. You will learn techniques that will help you to set up end-to-end traceability of your code changes from design through to release. Whether you are deploying software on-premise or in the cloud in App Service, Functions, or Azure VMs, this book will help you learn release management techniques to reduce release failures. Next, you will be able to secure application configuration by using Azure KeyVault. You will also learn how to create and release extensions to the Azure DevOps marketplace and reach million developer ecosystem for feedback. The working extension samples will allow you to iterate changes in your extensions easily and release updates to the marketplace quickly. By the end of this book, techniques provided in the book will help you break down the invisible silos between your software development teams. This will transform you from being a good software development team to an elite modern cross functional software development team. What you will learn * Set up a team project for an Agile delivery team, importing requirements from Excel * Plan,track, and monitor progress using self updating boards, Sprint and Kanban boards * Unlock the features of Git by using branch policies, Git pull requests, forks, and Git hooks * Build and release .NET core, SQL and Node.js applications using Azure Pipeline * Automate testing by integrating Microsoft and open source testing frameworks * Extend Azure DevOps Server to a million developer ecosystem Who this book is for This book is for anyone looking to succeed with DevOps. The techniques in this book apply to all roles of the software development lifecycle including developers, testers, architects, configuration analysts, site reliability engineers and release managers. If you are a new user you’ll learn how to get started; if you are an experienced user you’ll learn how to launch your project into a modern and mature DevOps enabled software development team.

Apply cloud native patterns and practices to deliver responsive, resilient, elastic, and message-driven systems with confidence Key Features * Discover best practices for applying cloud native patterns to your cloud applications * Explore ways to effectively plan resources and technology stacks for high security and fault tolerance * Gain insight into core architectural principles using real-world examples Book Description Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: * Cloud Native Development Patterns and Best Practices by John Gilbert * Cloud Native Architectures by Erik Farr et al. What you will learn * Understand the difference between cloud native and traditional architecture * Automate security controls and configuration management * Minimize risk by evolving your monolithic systems into cloud native applications * Explore the aspects of migration, when and why to use it * Apply modern delivery and testing methods to continuously deliver production code * Enable massive scaling by turning your database inside out Who this book is for This Learning Path is designed for developers who want to progress into building cloud native systems and are keen to learn the patterns involved. Software architects, who are keen on designing scalable and highly available cloud native applications, will also find this Learning Path very useful. To easily grasp these concepts, you will need basic knowledge of programming and cloud computing.

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