Get up to speed with various penetration testing techniques and resolve security threats of varying complexity Key Features * Enhance your penetration testing skills to tackle security threats * Learn to gather information, find vulnerabilities, and exploit enterprise defenses * Navigate secured systems with the most up-to-date version of Kali Linux (2019.1) and Metasploit (5.0.0) Book Description Sending information via the internet is not entirely private, as evidenced by the rise in hacking, malware attacks, and security threats. With the help of this book, you'll learn crucial penetration testing techniques to help you evaluate enterprise defenses. You'll start by understanding each stage of pentesting and deploying target virtual machines, including Linux and Windows. Next, the book will guide you through performing intermediate penetration testing in a controlled environment. With the help of practical use cases, you'll also be able to implement your learning in real-world scenarios. By studying everything from setting up your lab, information gathering and password attacks, through to social engineering and post exploitation, you'll be able to successfully overcome security threats. The book will even help you leverage the best tools, such as Kali Linux, Metasploit, Burp Suite, and other open source pentesting tools to perform these techniques. Toward the later chapters, you'll focus on best practices to quickly resolve security threats. By the end of this book, you'll be well versed with various penetration testing techniques so as to be able to tackle security threats effectively What you will learn * Perform entry-level penetration tests by learning various concepts and techniques * Understand both common and not-so-common vulnerabilities from an attacker's perspective * Get familiar with intermediate attack methods that can be used in real-world scenarios * Understand how vulnerabilities are created by developers and how to fix some of them at source code level * Become well versed with basic tools for ethical hacking purposes * Exploit known vulnerable services with tools such as Metasploit Who this book is for If you’re just getting started with penetration testing and want to explore various security domains, this book is for you. Security professionals, network engineers, and amateur ethical hackers will also find this book useful. Prior knowledge of penetration testing and ethical hacking is not necessary.

Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features * Perform time series analysis and forecasting using R packages such as Forecast and h2o * Develop models and find patterns to create visualizations using the TSstudio and plotly packages * Master statistics and implement time-series methods using examples mentioned Book Description Time series analysis is the art of extracting meaningful insights from, and revealing patterns in, time series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time series analysis with R and lays the foundations you need to build forecasting models. You will learn how to preprocess raw time series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book delves into traditional forecasting models such as time series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also cover advanced time series regression models with machine learning algorithms such as Random Forest and Gradient Boosting Machine using the h2o package. By the end of this book, you will have the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods. What you will learn * Visualize time series data and derive better insights * Explore auto-correlation and master statistical techniques * Use time series analysis tools from the stats, TSstudio, and forecast packages * Explore and identify seasonal and correlation patterns * Work with different time series formats in R * Explore time series models such as ARIMA, Holt-Winters, and more * Evaluate high-performance forecasting solutions Who this book is for Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.

Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills Key Features * Speed up your data analysis projects using powerful R packages and techniques * Create multiple hands-on data analysis projects using real-world data * Discover and practice graphical exploratory analysis techniques across domains Book Description Hands-On Exploratory Data Analysis with R will help you build not just a foundation but also expertise in the elementary ways to analyze data. You will learn how to understand your data and summarize its main characteristics. You'll also uncover the structure of your data, and you'll learn graphical and numerical techniques using the R language. This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will learn how to set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using tools such as DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems. By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, identify hidden insights, and present your results in a business context. What you will learn * Learn powerful R techniques to speed up your data analysis projects * Import, clean, and explore data using powerful R packages * Practice graphical exploratory analysis techniques * Create informative data analysis reports using ggplot2 * Identify and clean missing and erroneous data * Explore data analysis techniques to analyze multi-factor datasets Who this book is for Hands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data engineer, software engineer, or product manager, this book will sharpen your skills in the complete workflow of exploratory data analysis.

Learn how to use Unreal Engine 4 by building 3D and multiplayer games using Blueprints Key Features * Learn the fundamentals of Unreal Engine such as project templates, Blueprints, and C++ * Learn to design games; use UMG to create menus and HUDs, and replication to create multiplayer games * Build dynamic game elements using Animation Blueprints and Behavior Trees Book Description Unreal Engine is a popular game engine for developers to build high-end 2D and 3D games. This book is a practical guide, starting off by quickly introducing you to the Unreal Engine 4 (UE4) ecosystem. You will learn how to create Blueprints and C++ code to define your game's functionality. You will be familiarized with the core systems of UE4 such as UMG, Animation Blueprints, and Behavior Trees. You will also learn how to use replication to create multiplayer games. By the end of this book, you will have a broad, solid knowledge base to expand upon on your journey with UE4. What you will learn * Use project templates to give your game a head start * Create custom Blueprints and C++ classes and extend from Epic's base classes * Use UMG to create menus and HUDs for your game * Create more dynamic characters using Animation Blueprints * Learn how to create complex AI with Behavior Trees * Use replication to create multiplayer games * Optimize, test, and deploy a UE4 project Who this book is for Readers who already have some game development experience and Unity users who would like to try UE4 will all benefit from this book. Knowledge of basic Object-Oriented Programming topics such as variables, functions, and classes is assumed.

Enhance your skills in building scalable infrastructure for your cloud-based applications Key Features * Learn to design a scalable architecture by building continuous integration (CI) pipelines with Kubernetes * Get an in-depth understanding of role-based access control (RBAC), continuous deployment (CD), and observability * Monitor a Kubernetes cluster with Prometheus and Grafana Book Description Kubernetes is among the most popular open-source platforms for automating the deployment, scaling, and operations of application containers across clusters of hosts, providing a container-centric infrastructure. Hands-On Microservices with Kubernetes starts by providing you with in-depth insights into the synergy between Kubernetes and microservices. You will learn how to use Delinkcious, which will serve as a live lab throughout the book to help you understand microservices and Kubernetes concepts in the context of a real-world application. Next, you will get up to speed with setting up a CI/CD pipeline and configuring microservices using Kubernetes ConfigMaps. As you cover later chapters, you will gain hands-on experience in securing microservices, and implementing REST, gRPC APIs, and a Delinkcious data store. In addition to this, you’ll explore the Nuclio project, run a serverless task on Kubernetes, and manage and implement data-intensive tests. Toward the concluding chapters, you’ll deploy microservices on Kubernetes and learn to maintain a well-monitored system. Finally, you’ll discover the importance of service meshes and how to incorporate Istio into the Delinkcious cluster. By the end of this book, you’ll have gained the skills you need to implement microservices on Kubernetes with the help of effective tools and best practices. What you will learn * Understand the synergy between Kubernetes and microservices * Create a complete CI/CD pipeline for your microservices on Kubernetes * Develop microservices on Kubernetes with the Go kit framework using best practices * Manage and monitor your system using Kubernetes and open-source tools * Expose your services through REST and gRPC APIs * Implement and deploy serverless functions as a service * Externalize authentication, authorization and traffic shaping using a service mesh * Run a Kubernetes cluster in the cloud on Google Kubernetes Engine Who this book is for This book is for developers, DevOps engineers, or anyone who wants to develop large-scale microservice-based systems on top of Kubernetes. If you are looking to use Kubernetes on live production projects or want to migrate existing systems to a modern containerized microservices system, then this book is for you. Coding skills, together with some knowledge of Docker, Kubernetes, and cloud concepts will be useful.

Become an expert at managing enterprise identity infrastructure by leveraging Active Directory Key Features * Explore the new features in Active Directory Domain Service * Manage your Active Directory services for Windows Server 2016 effectively * Automate administrative tasks in Active Directory using PowerShell Core 6.x Book Description Active Directory (AD) is a centralized and standardized system that automates networked management of user data, security, and distributed resources and enables inter-operation with other directories. This book will first help you brush up on the AD architecture and fundamentals, before guiding you through core components, such as sites, trust relationships, objects, and attributes. You will then explore AD schemas, LDAP, RMS, and security best practices to understand objects and components and how they can be used effectively. Next, the book will provide extensive coverage of AD Domain Services and Federation Services for Windows Server 2016, and help you explore their new features. Furthermore, you will learn to manage your identity infrastructure for a hybrid cloud setup. All this will help you design, plan, deploy, manage operations, and troubleshoot your enterprise identity infrastructure in a secure and effective manner. You’ll later discover Azure AD Module, and learn to automate administrative tasks using PowerShell cmdlets. All along, this updated second edition will cover content based on the latest version of Active Directory, PowerShell 5.1 and LDAP. By the end of this book, you’ll be well versed with best practices and troubleshooting techniques for improving security and performance in identity infrastructures. What you will learn * Design your Hybrid AD environment by evaluating business and technology requirements * Protect sensitive data in a hybrid environment using Azure Information Protection * Explore advanced functionalities of the schema * Learn about Flexible Single Master Operation (FSMO) roles and their placement * Install and migrate Active Directory from older versions to Active Directory 2016 * Control users, groups, and devices effectively * Design your OU structure in the most effective way * Integrate Azure AD with Active Directory Domain Services for a hybrid setup Who this book is for If you are an Active Directory administrator, system administrator, or network professional who has basic knowledge of Active Directory and is looking to become an expert in this topic, this book is for you.

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

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

Learn the fundamentals, practical applications, and latest features of C# 8.0 and .NET Core 3.0 from expert teacher Mark J. Price. Key Features * Build modern, cross-platform applications with .NET Core 3.0 * Get up to speed with C#, and up to date with all the latest features of C# 8.0 * Start creating professional web applications with ASP.NET Core 3.0 Book Description In C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development, Fourth Edition, expert teacher Mark J. Price gives you everything you need to start programming C# applications. This latest edition uses the popular Visual Studio Code editor to work across all major operating systems. It is fully updated and expanded with new chapters on Content Management Systems (CMS) and machine learning with ML.NET. The book covers all the topics you need. Part 1 teaches the fundamentals of C#, including object-oriented programming, and new C# 8.0 features such as nullable reference types, simplified switch pattern matching, and default interface methods. Part 2 covers the .NET Standard APIs, such as managing and querying data, monitoring and improving performance, working with the filesystem, async streams, serialization, and encryption. Part 3 provides examples of cross-platform applications you can build and deploy, such as web apps using ASP.NET Core or mobile apps using Xamarin.Forms. The book introduces three technologies for building Windows desktop applications including Windows Forms, Windows Presentation Foundation (WPF), and Universal Windows Platform (UWP) apps, as well as web applications, web services, and mobile apps. What you will learn * Build cross-platform applications for Windows, macOS, Linux, iOS, and Android * Explore application development with C# 8.0 and .NET Core 3.0 * Explore ASP.NET Core 3.0 and create professional web applications * Learn object-oriented programming and C# multitasking * Query and manipulate data using LINQ * Use Entity Framework Core and work with relational databases * Discover Windows app development using the Universal Windows Platform and XAML * Build mobile applications for iOS and Android using Xamarin.Forms Who this book is for Readers with some prior programming experience or with a science, technology, engineering, or mathematics (STEM) background, who want to gain a solid foundation with C# 8.0 and .NET Core 3.0.

Integrate open source data analytics and build business intelligence on SQL databases with Apache Superset. The quick, intuitive nature for data visualization in a web application makes it easy for creating interactive dashboards. Key Features *Work with Apache Superset's rich set of data visualizations *Create interactive dashboards and data storytelling *Easily explore data Book Description Apache Superset is a modern, open source, enterprise-ready business intelligence (BI) web application. With the help of this book, you will see how Superset integrates with popular databases like Postgres, Google BigQuery, Snowflake, and MySQL. You will learn to create real time data visualizations and dashboards on modern web browsers for your organization using Superset. First, we look at the fundamentals of Superset, and then get it up and running. You'll go through the requisite installation, configuration, and deployment. Then, we will discuss different columnar data types, analytics, and the visualizations available. You'll also see the security tools available to the administrator to keep your data safe. You will learn how to visualize relationships as graphs instead of coordinates on plain orthogonal axes. This will help you when you upload your own entity relationship dataset and analyze the dataset in new, different ways. You will also see how to analyze geographical regions by working with location data. Finally, we cover a set of tutorials on dashboard designs frequently used by analysts, business intelligence professionals, and developers. What you will learn *Get to grips with the fundamentals of data exploration using Superset *Set up a working instance of Superset on cloud services like Google Compute Engine *Integrate Superset with SQL databases *Build dashboards with Superset *Calculate statistics in Superset for numerical, categorical, or text data *Understand visualization techniques, filtering, and grouping by aggregation *Manage user roles and permissions in Superset *Work with SQL Lab Who this book is for This book is for data analysts, BI professionals, and developers who want to learn Apache Superset. If you want to create interactive dashboards from SQL databases, this book is what you need. Working knowledge of Python will be an advantage but not necessary to understand this book.

Take your comics and illustrations to the next level with the powerful art tools in Clip Studio Paint 1.8 Key Features *Overcome “interface overwhelm” with a practical breakdown of the Clip Studio interface *Comprehensive guide on the Clip Studio Paint with detailed coverage of all the tools and concepts of designing comics *Streamline your workflow to create faster and easier using Clip Studio’s features Book Description Clip Studio Paint, the successor to Manga Studio, is used by over four million illustrators and comic creators around the world. This book will guide you through every step of learning this software, from system requirements and installation, all the way through to exporting your work for print or the web. Learn how to create new documents, customize tools to fit your working style, use ruler tools to create anything from straight lines to intricate backgrounds, add 3D elements, create comic panels using the specialized panel tools, utilize screentones and materials, add text and word balloons to your comics, create sound effects, easily flat and color your comics using reference layers, and bring your drawings to life using the animation features. By the end of this book, you will be able to navigate the Clip Studio Interface and program preferences, customize the various tools, and be able to create your own black-and-white and color illustrations and comics from start to finish. What you will learn *Understand the differences between Clip Studio Paint Pro and EX *Discover how to navigate and customize the user interface *Creating custom tools that fit your unique style of illustration *Using the ruler tools to create intricate perspective shots and complex symmetry *Discover how to use 3D elements in your work *Learn how to create lettering and word balloons to bring your comic stories to life *Understand the process of digital art creation from pencils to inks to color *Understand how to use the animation tools available in Clip Studio Paint Who this book is for If you are a beginning digital artist or are switching to Clip Studio from another graphics software, this book is for you. This book is excellent for those with no knowledge of digital art up to intermediate users looking to explore the unique features of Clip Studio Paint.

A fast paced guide for JavaScript developers for writing safe, fast, and reusable code by leveraging ResaonML's strong static type system Key Features *Reduce code errors with the power of type systems *Employ static typechecking and genericity to promote code reuse and consistency *Understand functional programming which is the foundation of type-driven development Book Description Type-driven development is an approach that uses a static type system to achieve results including safety and efficiency. Types are used to express relationships and other assumptions directly in the code, and these assumptions are enforced by the compiler before the code is run. Learn Type-Driven Development covers how to use these type systems to check the logical consistency of your code. This book begins with the basic idea behind type-driven development. You’ll learn about values (or terms) and how they contrast with types. As you progress through the chapters, you’ll cover how to combine types and values inside modules and build structured types out of simpler ones. You’ll then understand how to express choices or alternatives directly in the type system using variants, polymorphic variants, and generalized algebraic data types. You’ll also get to grips with sum types, build sophisticated data types from generics, and explore functions that express change in the types of values. In the concluding chapters, you’ll cover advanced techniques for code reuse, such as parametric polymorphism and subtyping. By end of this book, you will have learned how to iterate through a type-driven process of solving coding problems using static types, together with dynamic behavior, to obtain more safety and speed. What you will learn *Use static types to capture information, making programs safer and faster *Learn ReasonML from experienced type-driven developers *Enhance safety by simply using basic types *Understand the most important type-driven concepts with simple examples *Explore a design space using static typing and find the best way to express your system rules *Use static types and dynamic runtime in harmony to write even safer and faster code Who this book is for If you’re a programmer working with dynamically typed languages and are looking for ways to mitigate production runtime errors, Learn Type-Driven Development is for you. You’ll also find this book helpful if you’re a programmer working with statically typed languages looking for increased safety and improved performance.

Explore various Azure services to build solutions that leverage effective design patterns Key Features *Create, deploy, and host cloud applications on Azure *Understand various Azure services that help you host serverless applications *Explore practical examples to help you secure and troubleshoot your cloud environment Book Description Azure is one of the leading public cloud service providers. Thanks to a number of Azure service updates, it continues to make advances in the realm of cloud computing. Learn Microsoft Azure starts with the fundamentals of cloud computing. You will learn to configure and set up the Azure infrastructure. As you make your way through the book, you'll explore Azure services, along with working on virtual memory systems (VMS) and deployment models. You will understand various services in the Azure ecosystem, such as Azure IoT and Azure Analytics, among others. An easy-to-follow introduction to various cloud design patterns will also add to your efficiency in designing cloud solutions. In the concluding chapters, you'll secure your virtual networks using Network security groups and configure Azure Active Directory (Azure AD) to set a custom domain name and company profile. By the end of this book, you will have learned to secure and troubleshoot your Azure cloud environment and be fully aware of best practices for Azure cloud administration. What you will learn *Understand the cloud services offered by Azure *Design storage and networks in Azure for your Azure VM *Work with web apps and Azure SQL databases *Build your identity management solutions on Azure using Azure AD *Monitor, protect, and automate your Azure services using Operation Management Suite (OMS) *Implement OMS for Azure services Who this book is for Learn Microsoft Azure is for administrators, cloud engineers, and developers who want to get started with using Azure as their cloud platform and build cloud-based applications for their enterprises.

Build real-world projects like a smart contract deployment platform, betting apps, wallet services, and much more using blockchain Key Features *Apply blockchain principles and features for making your life and business better *Understand Ethereum for smart contracts and DApp deployment *Tackle current and future challenges and problems relating to blockchain Book Description Blockchain applications provide a single-shared ledger to eliminate trust issues involving multiple stakeholders. It is the main technical innovation of Bitcoin, where it serves as the public ledger for Bitcoin transactions. Blockchain Developer's Guide takes you through the electrifying world of blockchain technology. It begins with the basic design of a blockchain and elaborates concepts, such as Initial Coin Offerings (ICOs), tokens, smart contracts, and other related terminologies. You will then explore the components of Ethereum, such as Ether tokens, transactions, and smart contracts that you need to build simple DApps. Blockchain Developer's Guide also explains why you must specifically use Solidity for Ethereum-based projects and lets you explore different blockchains with easy-to-follow examples. You will learn a wide range of concepts - beginning with cryptography in cryptocurrencies and including ether security, mining, and smart contracts. You will learn how to use web sockets and various API services for Ethereum. By the end of this Learning Path, you will be able to build efficient decentralized applications. This Learning Path includes content from the following Packt products: *Blockchain Quick Reference by Brenn Hill, Samanyu Chopra, Paul Valencourt *Building Blockchain Projects by Narayan Prusty What you will learn *Understand how various components of the blockchain architecture work *Get familiar with cryptography and the mechanics behind blockchain *Apply consensus protocol to determine the business sustainability *Understand what ICOs and crypto-mining are, and how they work Who this book is for Blockchain Developer's Guide is for you if you want to get to grips with the blockchain technology and develop your own distributed applications. It is also designed for those who want to polish their existing knowledge regarding the various pillars of the blockchain ecosystem. Prior exposure to an object-oriented programming language such as JavaScript is needed.

The essential blueprints and workflow you need to build successful AI business applications Key Features *Learn and master the essential blueprints to program AI for real-world business applications *Gain insights into how modern AI and machine learning solve core business challenges *Acquire practical techniques and a workflow that can build AI applications using state-of-the-art software libraries *Work with a practical, code-based strategy for creating successful AI solutions in your business Book Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learn *An essential toolbox of blueprints and advanced techniques for building AI business applications *How to design and deploy AI applications that meet today’s business needs *A workflow from first design stages to practical code solutions in your next AI projects *Solutions for AI projects that involve social media analytics and recommendation engines *Practical projects and techniques for sentiment analysis and helpful chatbots *A blueprint for AI projects that recommend products based on customer purchasing habits *How to prepare yourself for the next decade of AI and machine learning advancements Who this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.

Get into the world of smart data security using machine learning algorithms and Python libraries Key Features *Learn machine learning algorithms and cybersecurity fundamentals *Automate your daily workflow by applying use cases to many facets of security *Implement smart machine learning solutions to detect various cybersecurity problems Book Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learn *Use machine learning algorithms with complex datasets to implement cybersecurity concepts *Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems *Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA *Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes *Use TensorFlow in the cybersecurity domain and implement real-world examples *Learn how machine learning and Python can be used in complex cyber issues Who this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

Over 100 recipes to get up and running with the modern Linux administration ecosystem Key Features *Understand and implement the core system administration tasks in Linux *Discover tools and techniques to troubleshoot your Linux system *Maintain a healthy system with good security and backup practices Book Description Linux is one of the most widely used operating systems among system administrators,and even modern application and server development is heavily reliant on the Linux platform. The Linux Administration Cookbook is your go-to guide to get started on your Linux journey. It will help you understand what that strange little server is doing in the corner of your office, what the mysterious virtual machine languishing in Azure is crunching through, what that circuit-board-like thing is doing under your office TV, and why the LEDs on it are blinking rapidly. This book will get you started with administering Linux, giving you the knowledge and tools you need to troubleshoot day-to-day problems, ranging from a Raspberry Pi to a server in Azure, while giving you a good understanding of the fundamentals of how GNU/Linux works. Through the course of the book, you’ll install and configure a system, while the author regales you with errors and anecdotes from his vast experience as a data center hardware engineer, systems administrator, and DevOps consultant. By the end of the book, you will have gained practical knowledge of Linux, which will serve as a bedrock for learning Linux administration and aid you in your Linux journey. What you will learn *Install and manage a Linux server, both locally and in the cloud *Understand how to perform administration across all Linux distros *Work through evolving concepts such as IaaS versus PaaS, containers, and automation *Explore security and configuration best practices *Troubleshoot your system if something goes wrong *Discover and mitigate hardware issues, such as faulty memory and failing drives Who this book is for If you are a system engineer or system administrator with basic experience of working with Linux, this book is for you.

Design and implement professional level programs by exploring modern data structures and algorithms in Rust. Key Features * Use data structures such as arrays, stacks, trees, lists and graphs with real-world examples * Learn the functional and reactive implementations of the traditional data structures * Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Book Description Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. What you will learn * Design and implement complex data structures in Rust * Analyze, implement, and improve searching and sorting algorithms in Rust * Create and use well-tested and reusable components with Rust * Understand the basics of multithreaded programming and advanced algorithm design * Become familiar with application profiling based on benchmarking and testing * Explore the borrowing complexity of implementing algorithms Who this book is for This book is for developers seeking to use Rust solutions in a practical/professional setting; who wants to learn essential Data Structures and Algorithms in Rust. It is for developers with basic Rust language knowledge, some experience in other programming languages is required.

Leverage Elastic Stack’s machine learning features to gain valuable insight from your data Key Features * Combine machine learning with the analytic capabilities of Elastic Stack * Analyze large volumes of search data and gain actionable insight from them * Use external analytical tools with your Elastic Stack to improve its performance Book Description Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly. What you will learn * Install the Elastic Stack to use machine learning features * Understand how Elastic machine learning is used to detect a variety of anomaly types * Apply effective anomaly detection to IT operations and security analytics * Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting * Combine your created jobs to correlate anomalies of different layers of infrastructure * Learn various tips and tricks to get the most out of Elastic machine learning Who this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.

Build smarter systems by combining artificial intelligence and the Internet of Things—two of the most talked about topics today Key Features * Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data * Process IoT data and predict outcomes in real time to build smart IoT models * Cover practical case studies on industrial IoT, smart cities, and home automation Book Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learn * Apply different AI techniques including machine learning and deep learning using TensorFlow and Keras * Access and process data from various distributed sources * Perform supervised and unsupervised machine learning for IoT data * Implement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platforms * Forecast time-series data using deep learning methods * Implementing AI from case studies in Personal IoT, Industrial IoT, and Smart Cities * Gain unique insights from data obtained from wearable devices and smart devices Who this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how popular artificial intelligence (AI) techniques can be used in the Internet of Things domain, this book will also be of benefit. A basic understanding of machine learning concepts will be required to get the best out of this book.

Discover how cloud-native microservice architecture helps you to build dynamically scalable applications by using the most widely used and adopted runtime environments Key Features * Build robust cloud-native applications using a variety of tools * Understand how to configure both Amazon Web Services (AWS) and Docker clouds for high availability * Explore common design patterns used in building and deploying microservices architecture. Book Description Businesses today are evolving rapidly, and developers now face the challenge of building applications that are resilient, flexible, and native to the cloud. To achieve this, you'll need to be aware of the environment, tools, and resources that you're coding against. The book will begin by introducing you to cloud-native architecture and simplifying the major concepts. You'll learn to build microservices in Jakarta EE using MicroProfile with Thorntail and Narayana LRA. You'll then delve into cloud-native application x-rays, understanding the MicroProfile specification and the implementation/testing of microservices. As you progress further, you'll focus on continuous integration and continuous delivery, in addition to learning how to dockerize your services. You'll also cover concepts and techniques relating to security, monitoring, and troubleshooting problems that might occur with applications after you've written them. By the end of this book, you will be equipped with the skills you need to build highly resilient applications using cloud-native microservice architecture. What you will learn * Integrate reactive principles in MicroProfile microservices architecture * Explore the 12-factors-app paradigm and its implications * Get the best out of Java versions 8 and 9 to implement a microservice based on Thorntail * Understand what OpenShift is and why it is so important for an elastic architecture * Build a Linux container image using Docker and scale the application using Kubernetes * Implement various patterns such as, Circuit Breaker and bulkheads * Get to grips with the DevOps methodology using continuous integration (CI) and continuous deployment (CD) Who this book is for This book is for developers with basic knowledge of Java EE and HTTP-based application principles who want to learn how to build, test and scale Java EE microservices. No prior experience of writing microservices in Java EE is required.