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.

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.

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.

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.

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.

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.

Begin your iOS 12 app development journey with this practical guide Key Features *Kick-start your iOS programming career and have fun building iOS apps of your choice *Get to grips with Xcode 10 and Swift 4.2, the building blocks of iOS development *Discover the latest features of iOS 12 - SiriKit, notifications, and much more Book Description Want to build iOS 12 applications from scratch with the latest Swift 4.2 language and Xcode 10 by your side? Forget sifting through tutorials and blog posts; this book is a direct route to iOS development, taking you through the basics and showing you how to put principles into practice. Take advantage of this developer-friendly guide and start building applications that may just take the App Store by storm! If you’re already an experienced programmer, you can jump right in and learn the latest iOS 12 features. For beginners, this book starts by introducing you to iOS development as you learn Xcode and Swift. You'll also study advanced iOS design topics, such as gestures and animations, to give your app the edge. You’ll explore the latest Swift 4.2 and iOS 12 developments by incorporating new features, such as the latest in notifications, custom-UI notifications, maps, and the recent additions in Sirikit. The book will guide you in using TestFlight to quickly get to grips with everything you need to get your project on the App Store. By the end of this book, you'll be ready to start building your own cool iOS applications confidently. What you will learn *Explore the distinctive design principles that define the iOS user experience *Navigate panels within an Xcode project *Use the latest Xcode asset catalogue of Xcode 10 *Create a playgrounds project within your projects and understand how Ranges and Control flow work *Study operations with integers and work your way through if statements *Build a responsive UI and add privacy to your custom-rich notifications *Set up Sirikit to add voice for Siri shortcuts *Collect valuable feedback with TestFlight before releasing your apps on the App Store Who this book is for This book is for you if you are completely new to Swift, iOS, or programming and want to make iOS applications. However, you’ll also find this book useful if you’re an experienced programmer looking to explore the latest iOS 12 features.

Don't waste your energy thinking about servers; use AWS to build enterprise-grade serverless applications. Key Features *Learn how to quickly and easily go serverless *Explore AWS and Lambda: the first building blocks of serverless applications on AWS *Study different approaches to deploy and maintain serverless applications Book Description Serverless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You'll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda. This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You’ll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You'll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you’ll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight serverless architectures. By the end of the book, you will be ready to create and run your first serverless application that takes advantage of the high availability, security, performance, and scalability of AWS. What you will learn *Explore AWS services for supporting a serverless environment *Set up AWS services to make applications scalable and highly available *Deploy a static website with a serverless architecture *Build your first serverless web application *Study the changes in a deployed serverless web application *Apply best practices to ensure overall security, availability, and reliability Who this book is for This book is for you if you want to develop serverless applications and have some prior coding experience. Though no prior experience of AWS is needed, basic knowledge of Java or Node.js will be an added advantage.

Master shell basics and Unix tools and discover easy commands to perform complex tasks with speed Key Features *Learn why the Bash shell is widely used on Linux and iOS *Explore advanced shell concepts, such as pipes and redirection *Understand how to use Unix command-line tools as building blocks for different tasks Book Description The most basic interface to a computer—the command line—remains the most flexible and powerful way of processing data and performing and automating various day-to-day tasks. Command Line Fundamentals begins by exploring the basics, and then focuses on the most common tool, the Bash shell (which is standard on all Linux and iOS systems). As you make your way through the book, you'll explore the traditional Unix command-line programs as implemented by the GNU project. You'll also learn to use redirection and pipelines to assemble these programs to solve complex problems. By the end of this book, you'll have explored the basics of shell scripting, allowing you to easily and quickly automate tasks. What you will learn *Use the Bash shell to run commands *Utilize basic Unix utilities such as cat, tr, sort, and uniq *Explore shell wildcards to manage groups of files *Apply useful keyboard shortcuts in shell *Employ redirection and pipes to process data *Write both basic and advanced shell scripts to automate tasks Who this book is for Command Line Fundamentals is for programmers who use GUIs but want to understand how to use the command line to complete tasks faster.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features *Master the art of real-time big data processing and machine learning *Explore a wide range of use-cases to analyze large data *Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: *Mastering Apache Spark 2.x by Romeo Kienzler *Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla *Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn *Get to grips with all the features of Apache Spark 2.x *Perform highly optimized real-time big data processing *Use ML and DL techniques with Spark MLlib and third-party tools *Analyze structured and unstructured data using SparkSQL and GraphX *Understand tuning, debugging, and monitoring of big data applications *Build scalable and fault-tolerant streaming applications *Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

Gather detailed statistics and deploy impressive business solutions with Zabbix 4.0 Key Features *Experience the full impact of Zabbix 4.0, a useful and increasingly popular tool *Enhance your network’s performance and manage hosts and systems *A step-by-step guide to smarter network monitoring Book Description Zabbix 4 Network Monitoring is the perfect starting point for monitoring the performance of your network devices and applications with Zabbix. Even if you’ve never used a monitoring solution before, this book will get you up and running quickly. You’ll learn to monitor more sophisticated operations with ease and soon feel in complete control of your network, ready to meet any challenges you might face. Starting with the installation, you will discover the new features in Zabbix 4.0. You will then get to grips with native Zabbix agents and Simple Network Management Protocol (SNMP) devices. You will also explore Zabbix's integrated functionality for monitoring Java application servers and VMware. This book also covers notifications, permission management, system maintenance, and troubleshooting, so you can be confident that every potential challenge and task is under your control. If you're working with larger environments, you'll also be able to find out more about distributed data collection using Zabbix proxies. Once you're confident and ready to put these concepts into practice, you will understand how to optimize and improve performance. Troubleshooting network issues is vital for anyone working with Zabbix, so the book also helps you work through any technical snags and glitches you might face. By the end of this book, you will have learned more advanced techniques to fine-tune your system and make sure it is in a healthy state. What you will learn *Install Zabbix server and an agent from source *Manage hosts, users, and permissions while acting upon monitored conditions *Visualize data with the help of ad hoc graphs, custom graphs, and maps *Simplify complex configurations and learn to automate them *Monitor everything from web pages to IPMI devices and Java applications to VMware stats *Configure Zabbix to send alerts including problem severity and time periods *Troubleshoot any network issue Who this book is for If you're new to Zabbix look no further than this book. Zabbix 4 Network Monitoring is for system and network administrators who are looking to put their knowledge to work with Zabbix 4.0.

Implement real-world decentralized applications using Python, Vyper, Populus, and Ethereum Key Features * Stay up-to-date with everything you need to know about the blockchain ecosystem * Implement smart contracts, wallets, and decentralized applications(DApps) using Python libraries * Get deeper insights into storing content in a distributed storage platform Book Description Blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions. This book serves as a practical guide to developing a full-fledged decentralized application with Python to interact with the various building blocks of blockchain applications. Hands-On Blockchain for Python Developers starts by demonstrating how blockchain technology and cryptocurrency hashing works. You will understand the fundamentals and benefits of smart contracts such as censorship resistance and transaction accuracy. As you steadily progress, you'll go on to build smart contracts using Vyper, which has a similar syntax to Python. This experience will further help you unravel the other benefits of smart contracts, including reliable storage and backup, and efficiency. You'll also use web3.py to interact with smart contracts and leverage the power of both the web3.py and Populus framework to build decentralized applications that offer security and seamless integration with cryptocurrencies. As you explore later chapters, you'll learn how to create your own token on top of Ethereum and build a cryptocurrency wallet graphical user interface (GUI) that can handle Ethereum and Ethereum Request for Comments (ERC-20) tokens using the PySide2 library. This will enable users to seamlessly store, send, and receive digital money. Toward the end, you'll implement InterPlanetary File System (IPFS) technology in your decentralized application to provide a peer-to-peer filesystem that can store and expose media. By the end of this book, you'll be well-versed in blockchain programming and be able to build end-to-end decentralized applications on a range of domains using Python. What you will learn * Understand blockchain technology and what makes it an immutable database * Use the features of web3.py API to interact with the smart contract * Create your own cryptocurrency and token in Ethereum using Vyper * Use IPFS features to store content on the decentralized storage platform * Implement a Twitter-like decentralized application with a desktop frontend * Build decentralized applications in the shape of console, web, and desktop applications Who this book is for If you are a Python developer who wants to enter the world of blockchain, Hands-On Blockchain for Python Developers is for you. The book will be your go-to guide to becoming well-versed with the blockchain ecosystem and building your own decentralized applications using Python and library support.

Master the concepts and techniques that will enable you to succeed on the SK0-004 exam the first time with the help of this study guide Key Features * Explore virtualisation, IPv4 & IPv6 networking, administration and more * Enhancing limited knowledge of server configuration and function * A study guide that covers the objectives for the certification examination Book Description CompTIA Server+ Certification is one of the top 5 IT certifications that is vendor neutral.System administrators opt for CompTIA server+ Certification to gain advanced knowledge of concepts including troubleshooting and networking. This book will initially start with the configuration of a basic network server and the configuration for each of its myriad roles. The next set of chapters will provide an overview of the responsibilities and tasks performed by a system administrator to manage and maintain a network server. Moving ahead, you will learn the basic security technologies, methods, and procedures that can be applied to a server and its network. Next, you will cover the troubleshooting procedures and methods in general, and specifically for hardware, software, networks, storage devices, and security applications. Toward the end of this book, we will cover a number of troubleshooting and security mitigation concepts for running admin servers with ease. This guide will be augmented by test questions and mock papers that will help you obtain the necessary certification. By the end of this book, you will be in a position to clear Server+ Certification with ease. What you will learn * Understand the purpose and role of a server in a computer network * Review computer hardware common to network servers * Detail the function and configuration of network operating systems * Describe the functions and tasks of network operating system administration * Explain the various data storage options on a computer network * Detail the need for, and the functioning and application of, network and server security * Describe the operational elements of a network provided by a server * Explain the processes and methods involved in troubleshooting server issues Who this book is for This book is targeted towards professionals seeking to gain the CompTIA Server+ certification. People coming from a Microsoft background with basic operating system and networking skills will also find this book useful. Basic experience working with system administration is mandatory.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key Features *Make a hands-on start in the fields of Big Data, Distributed Technologies and Machine Learning *Learn how to design, develop and interpret the results of common Machine Learning algorithms *Uncover hidden patterns in your data in order to derive real actionable insights and business value Book Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learn *Understand how Spark fits in the context of the big data ecosystem *Understand how to deploy and configure a local development environment using Apache Spark *Understand how to design supervised and unsupervised learning models *Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries *Design real-time machine learning pipelines in Apache Spark *Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms Who this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key Features *Solve practical large data and processing challenges with Kafka *Tackle data processing challenges like late events, windowing, and watermarking *Understand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQL Book Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learn *How to validate data with Kafka *Add information to existing data ?ows *Generate new information through message composition *Perform data validation and versioning with the Schema Registry *How to perform message Serialization and Deserialization *How to perform message Serialization and Deserialization *Process data streams with Kafka Streams *Understand the duality between tables and streams with KSQL Who this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.

Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key Features *Implement image classification and object detection using machine learning and deep learning *Perform image classification, object detection, image segmentation, and other Computer Vision tasks *Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn *Install and run major Computer Vision packages within Python *Apply powerful support vector machines for simple digit classification *Understand deep learning with TensorFlow *Build a deep learning classifier for general images *Use LSTMs for automated image captioning *Read text from real-world images *Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features *Understand the common architecture of different types of GANs *Train, optimize, and deploy GAN applications using TensorFlow and Keras *Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn *Structure a GAN architecture in pseudocode *Understand the common architecture for each of the GAN models you will build *Implement different GAN architectures in TensorFlow and Keras *Use different datasets to enable neural network functionality in GAN models *Combine different GAN models and learn how to fine-tune them *Produce a model that can take 2D images and produce 3D models *Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.

Learn how to use RxClojure to deal with stateful computations Key Features * Leverage the features of Functional Reactive Programming using Clojure * Create dataflow-based systems that are the building blocks of Reactive Programming * Use different Functional Reactive Programming frameworks, techniques, and patterns to solve real-world problems Book Description Reactive Programming is central to many concurrent systems, and can help make the process of developing highly concurrent, event-driven, and asynchronous applications simpler and less error-prone. This book will allow you to explore Reactive Programming in Clojure 1.9 and help you get to grips with some of its new features such as transducers, reader conditionals, additional string functions, direct linking, and socket servers. Hands-On Reactive Programming with Clojure starts by introducing you to Functional Reactive Programming (FRP) and its formulations, as well as showing you how it inspired Compositional Event Systems (CES). It then guides you in understanding Reactive Programming as well as learning how to develop your ability to work with time-varying values thanks to examples of reactive applications implemented in different frameworks. You'll also gain insight into some interesting Reactive design patterns such as the simple component, circuit breaker, request-response, and multiple-master replication. Finally, the book introduces microservices-based architecture in Clojure and closes with examples of unit testing frameworks. By the end of the book, you will have gained all the knowledge you need to create applications using different Reactive Programming approaches. What you will learn * Understand how to think in terms of time-varying values and event streams * Create, compose, and transform observable sequences using Reactive extensions * Build a CES framework from scratch using core.async as its foundation * Develop a simple ClojureScript game using Reagi * Integrate Om and RxJS in a web application * Implement a reactive API in Amazon Web Services (AWS) * Discover helpful approaches to backpressure and error handling * Get to grips with futures and their applications Who this book is for If you’re interested in using Reactive Programming to build asynchronous and concurrent applications, this is the book for you. Basic knowledge of Clojure programming is necessary to understand the concepts covered in this book.