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Practical Packet Analysis, 3E: Using Wireshark to Solve Real-World Network Problems
by Chris SandersIt’s easy to capture packets with Wireshark, the world’s most popular network sniffer, whether off the wire or from the air. But how do you use those packets to understand what’s happening on your network?Updated to cover Wireshark 2.x, the third edition of Practical Packet Analysis will teach you to make sense of your packet captures so that you can better troubleshoot network problems. You’ll find added coverage of IPv6 and SMTP, a new chapter on the powerful command line packet analyzers tcpdump and TShark, and an appendix on how to read and reference packet values using a packet map.Practical Packet Analysis will show you how to:–Monitor your network in real time and tap live network communications–Build customized capture and display filters–Use packet analysis to troubleshoot and resolve common network problems, like loss of connectivity, DNS issues, and slow speeds–Explore modern exploits and malware at the packet level–Extract files sent across a network from packet captures–Graph traffic patterns to visualize the data flowing across your network–Use advanced Wireshark features to understand confusing captures–Build statistics and reports to help you better explain technical network information to non-techiesNo matter what your level of experience is, Practical Packet Analysis will show you how to use Wireshark to make sense of any network and get things done.
Practical Paint.NET: The Powerful No-Cost Image Editor for Microsoft Windows
by Phillip WhittLearn to use the most up-to-date version of Paint.NET, the free, Windows-based program for image editing. This book is ideal for PC users who find Microsoft Paint too lacking, and Photoshop or GIMP too overwhelming. Paint.NET is a lightweight yet capable program that’s easy to navigate and is regularly updated. You’ll quickly become acquainted with this powerful, yet easy-to-learn program’s features; tools, layers, adjustments, and effects. See how to correct exposure, digitally retouch and repair damaged photos, and handle a broad spectrum of photo editing tasks—even how to colorize a black-and-white image. You’ll also learn how to create digital art using the Paint.NET drawing tools and effects. Practice files are provided with step-by-step instructions to jump into photo editing and art creation.Practical Paint.NET highlights this powerful program's rich set of features and capabilities providing you the pathway for just about any kind of image editing. Join the large community behind it today!What You'll LearnUse layers, which are essential in any professional quality image editing programAcquire and install plugins to maximize Paint.NET’s capabilitiesEnhance, retouch, and modify digital imagesCreate compelling digital artwork using the drawing tools and applying artistic filtersWho This Book Is ForWindows-based PC users who require the ability to edit digital images without the ongoing cost of subscription-based software, or complex open-source software. This group includes art or photography instructors (especially those in schools systems with limited budgets), small business owners, casual photographers, aspiring graphic designers, or anyone requiring a solid, basic editing program.
Practical Parallel Rendering
by Jessica KeyesMeeting the growing demands for speed and quality in rendering computer graphics images requires new techniques. Practical parallel rendering provides one of the most practical solutions. This book addresses the basic issues of rendering within a parallel or distributed computing environment, and considers the strengths and weaknesses of multiprocessor machines and networked render farms for graphics rendering. Case studies of working applications demonstrate, in detail, practical ways of dealing with complex issues involved in parallel processing.
Practical Plone 3: A Beginner's Guide to Building Powerful Websites
by Alex Clark Clayton ParkerThis is a beginner's practical guide that doesn't involve any code or programming concepts. You will learn by pointing and clicking on the options available in front of you. It includes easy-to-follow instructions and screenshots that will guide you through creating a powerful website. Each chapter stands alone and you need not go through all the chapters. You can pick and choose depending upon your requirements. If you want to get a Plone site up and running quickly and don't want to get involved in programming, this book is for you. This book is aimed at beginners, who want to configure and customize Plone to meet their content management needs. The book doesn't expect programming skills, although some knowledge of fundamental web concepts such as HTML and HTTP may be helpful.
Practical PostgreSQL
by Joshua D. Drake John C. WorsleyArguably the most capable of all the open source databases, PostgreSQL is an object-relational database management system first developed in 1977 by the University of California at Berkeley. In spite of its long history, this robust database suffers from a lack of easy-to-use documentation. Practical PostgreSQL fills that void with a fast-paced guide to installation, configuration, and usage. This comprehensive new volume shows you how to compile PostgreSQL from source, create a database, and configure PostgreSQL to accept client-server connections. It also covers the many advanced features, such as transactions, versioning, replication, and referential integrity that enable developers and DBAs to use PostgreSQL for serious business applications. The thorough introduction to PostgreSQL's PL/pgSQL programming language explains how you can use this very useful but under-documented feature to develop stored procedures and triggers. The book includes a complete command reference, and database administrators will appreciate the chapters on user management, database maintenance, and backup & recovery. With Practical PostgreSQL, you will discover quickly why this open source database is such a great open source alternative to proprietary products from Oracle, IBM, and Microsoft. Also included is a CD-ROM with Command Prompt's PostgreSQL Application Server, LXP. The CD covers LXP version 0.8.0 and PostgreSQL version 7.1.3.
Practical PowerShell Security and Compliance Center: Get to grips with effectively managing the Security and Compliance Center with PowerShell, 2nd Edition
by Damian ScolesLearn all the latest practices to build and enhance your PowerShell scripts and manage the Security and Compliance Center easily and efficiently Key Features Gather the latest information and new cmdlets to get started with PowerShell Discover innovative ways to construct useful scripts Learn how to manage SCC with PowerShell through real-world scenarios Book Description PowerShell is an integral part of Office 365. This updated edition shares tips, tricks, new cmdlets, and best practices for using PowerShell with the Security and Compliance Center. The book starts by covering the basic tools of PowerShell, such as PowerShell ISE and PowerShell repositories, and then goes on to teach you how to connect to the SCC using multi-factor authentication. You will manage role groups to layer security, before exploring the importance of information barriers. As you progress, you will orchestrate insider risk policies to protect your organization from malicious users with access to sensitive data. Next, the book will show you how to manage various devices using tenant policies and device access rules. Later chapters will delve into various reporting methods and explore options for troubleshooting scripts and best practices to produce better scripts. The book concludes with an overview of Microsoft Secure Score to help you measure your organization's security posture. By the end of this book, you'll have the latest information and new cmdlets to confidently manage the Security and Compliance Center (SCC) with PowerShell. What you will learn Enhance the script, test it, and move it into production Make your PowerShell scripts more usable and accessible Study directory synchronization and its applications Explore layers of security that prevent unauthorized access Use PowerShell to implement Data Loss Prevention (DLP) Understand compliance and how it can be managed with PowerShell Who this book is for If you are already managing Exchange and have some PowerShell experience, then this book is for you. Professionals who want to gain more proficiency in PowerShell but are unsure of how to approach it will also find this book useful. To get the most out of this book, you must have sufficient experience of working in PowerShell as the book is not a beginner's guide to PowerShell.
Practical Predictive Analytics
by Ralph WintersMake sense of your data and predict the unpredictable About This Book • A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics • Apply the principles and techniques of predictive analytics to effectively interpret big data • Solve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domains Who This Book Is For This book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected. What You Will Learn • Master the core predictive analytics algorithm which are used today in business • Learn to implement the six steps for a successful analytics project • Classify the right algorithm for your requirements • Use and apply predictive analytics to research problems in healthcare • Implement predictive analytics to retain and acquire your customers • Use text mining to understand unstructured data • Develop models on your own PC or in Spark/Hadoop environments • Implement predictive analytics products for customers In Detail This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data. Style and Approach This book takes a practical hands-on approach wherein the algorithms will be explained with the help of real-world use cases. It is written in a well-researched academic style which is a great mix of theoretical and practical information. Code examples are supplied for both theoretical concepts as well as for the case studies. Key references and summaries will be provided at the end of each chapter so that you can explore those topics on their own.
Practical Probabilistic Programming
by Avi PfefferSummaryPractical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to model application domains and then express those probabilistic models in code. Although PP can seem abstract, in this book you'll immediately work on practical examples, like using the Figaro language to build a spam filter and applying Bayesian and Markov networks, to diagnose computer system data problems and recover digital images. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyThe data you accumulate about your customers, products, and website users can help you not only to interpret your past, it can also help you predict your future! Probabilistic programming uses code to draw probabilistic inferences from data. By applying specialized algorithms, your programs assign degrees of probability to conclusions. This means you can forecast future events like sales trends, computer system failures, experimental outcomes, and many other critical concerns. About the BookPractical Probabilistic Programming introduces the working programmer to probabilistic programming. In this book, you’ll immediately work on practical examples like building a spam filter, diagnosing computer system data problems, and recovering digital images. You’ll discover probabilistic inference, where algorithms help make extended predictions about issues like social media usage. Along the way, you’ll learn to use functional-style programming for text analysis, object-oriented models to predict social phenomena like the spread of tweets, and open universe models to gauge real-life social media usage. The book also has chapters on how probabilistic models can help in decision making and modeling of dynamic systems. What's InsideIntroduction to probabilistic modelingWriting probabilistic programs in FigaroBuilding Bayesian networksPredicting product lifecyclesDecision-making algorithmsAbout the ReaderThis book assumes no prior exposure to probabilistic programming. Knowledge of Scala is helpful. About the AuthorAvi Pfeffer is the principal developer of the Figaro language for probabilistic programming. Table of ContentsPART 1 INTRODUCING PROBABILISTIC PROGRAMMING AND FIGAROProbabilistic programming in a nutshell A quick Figaro tutorial Creating a probabilistic programming application PART 2 WRITING PROBABILISTIC PROGRAMSProbabilistic models and probabilistic programs Modeling dependencies with Bayesian and Markov networks Using Scala and Figaro collections to build up models Object-oriented probabilistic modeling Modeling dynamic systems PART 3 INFERENCEThe three rules of probabilistic inference Factored inference algorithms Sampling algorithms Solving other inference tasks Dynamic reasoning and parameter learning
Practical Process Automation: Orchestration And Integration In Microservices And Cloud Native Architectures
by Bernd RueckerIn today's IT architectures, microservices and serverless functions play increasingly important roles in process automation. But how do you create meaningful, comprehensive, and connected business solutions when the individual components are decoupled and independent by design? Targeted at developers and architects, this book presents a framework through examples, practical advice, and use cases to help you design and automate complex processes.As systems are more distributed, asynchronous, and reactive, process automation requires state handling to deal with long-running interactions. Author Bernd Ruecker demonstrates how to leverage process automation technology like workflow engines to orchestrate software, humans, decisions, or bots.Learn how modern process automation compares to business process management, service-oriented architecture, batch processing, event streaming, and data pipeline solutionsUnderstand how to use workflow engines and executable process models with BPMNUnderstand the difference between orchestration and choreography and how to balance both
Practical Programming: An Introduction to Computer Science Using Python 3
by Jennifer Campbell Paul Gries Jason MontojoThis book is for anyone who wants to understand computer programming. You'll learn to program in a language that' s used in millions of smartphones, tablets, and PCs. You'll code along with the book, writing programs to solve real-world problems as you learn the fundamentals of programming using Python 3. You'll learn about design, algorithms, testing, and debugging, and come away with all the tools you need to produce quality code. In this second edition, we've updated almost all the material, incorporating the lessons we've learned over the past five years of teaching Python to people new to programming. You don't need any programming experience to get started. First, you'll get a detailed introduction to Python and to programming. You'll find out exactly what happens when your programs are executed. Through real-world examples, you'll learn how to work with numbers, text, big data sets, and files. Then you'll see how to create and use your own data types. The incremental examples show you the steps and missteps that happen while developing programs, so you know what to expect when you tackle a problem on your own. Inspired by "How to Design Programs" (HtDP), you'll learn a six-step recipe for designing functions, which helps you as you start to learn the concepts--and becomes an integral part of writing programs by the end. As you learn to use the fundamental programming tools in the first half of the book, you'll see how to document and organize your code so that you and other programmers can more easily read and understand it. Beyond the basics, you'll learn how to ensure that your programs are reliable, and how to work with databases, download data from the web automatically, and build user interfaces. Most importantly, you'll learn how to think like a professional programmer. <P><P><i>Advisory: Bookshare has learned that this book offers only partial accessibility. We have kept it in the collection because it is useful for some of our members. Benetech is actively working on projects to improve accessibility issues such as these.</i>
Practical Programming: An Introduction to Computer Science Using Python 3.6
by Jennifer Campbell Paul Gries Jason MontojoClassroom-tested by tens of thousands of students, this new edition of the bestselling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6--a language that's used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6.
Practical Project Initiation
by Karl E WiegersZero in on key project-initiation tasks--and build a solid foundation for successful software development. In this concise guide, critically-acclaimed author Karl E. Wiegers fills a void in project management literature by focusing on the activities that are essential--but often overlooked--for launching any project. Drawing on his extensive experience, Karl shares lessons learned, proven practices, and tools for getting your project off to the right start--and steering it to ultimate success. Lay a foundation for project success--discover how to: Effectively charter a project Define meaningful criteria for project success and product releases Negotiate achievable commitments for project teams and stakeholders Identify and document potential barriers to success--and manage project risks Apply the Wideband Delphi method for more accurate estimation Measure project performance and avoid common metrics traps Systematically apply lessons learned to future projects Companion Web site includes: Worksheets from inside the book Project document templates Resources for project initiation and process improvement
Practical Project Management for Building and Construction: Practical Project Management For Building And Construction (Esi International Project Management Ser. #11)
by Hans OttossonPractical Project Management for Building and Construction covers the 14 knowledge areas of project management that are essential for successful projects in the construction industry. For each knowledge area, it explains the processes for scope, time, risk, cost, and resource management. Filled with work and process flow diagrams, it demonstrates h
Practical Protein Bioinformatics
by Florencio Pazos Mónica ChagoyenThis book describes more than 60 web-accessible computational tools for protein analysis and is totally practical, with detailed explanations on how to use these tools and interpret their results and minimal mentions to their theoretical basis (only when that is required for making a better use of them). It covers a wide range of tools for dealing with different aspects of proteins, from their sequences, to their three-dimensional structures, and the biological networks they are immersed in. The selection of tools is based on the experience of the authors that lead a protein bioinformatics facility in a large research centre, with the additional constraint that the tools should be accessible through standard web browsers without requiring the local installation of specific software, command-line tools, etc. The web tools covered include those aimed to retrieve protein information, look for similar proteins, generate pair-wise and multiple sequence alignments of protein sequences, work with protein domains and motifs, study the phylogeny of a family of proteins, retrieve, manipulate and visualize protein three-dimensional structures, predict protein structural features as well as whole three-dimensional structures, extract biological information from protein structures, summarize large protein sets, study protein interaction and metabolic networks, etc. The book is associated to a dynamic web site that will reflect changes in the web addresses of the tools, updates of these, etc. It also contains QR codes that can be scanned with any device to direct its browser to the tool web site. This monograph will be most valuable for researchers in experimental labs without specific knowledge on bioinformatics or computing.
Practical Python AI Projects: Mathematical Models Of Optimization Problems With Google Or-tools
by Serge KrukDiscover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models,and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations.Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study.What You Will LearnBuild basic Python-based artificial intelligence (AI) applications Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suiteCreate several types of projects using Python and Google OR-ToolsWho This Book Is ForDevelopers and students who already have prior experience in Python coding. Some prior mathematical experience or comfort level may be helpful as well.
Practical Python Data Visualization: A Fast Track Approach To Learning Data Visualization With Python
by Ashwin PajankarQuickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book’s programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations. You’ll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python’s popular data visualization charting library. You’ll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You’ll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets. The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. With Practical Python Data Visualization you’ll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.What You'll LearnReview practical aspects of Python Data Visualization with programming-friendly abstractions Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu Visualize COVID-19 data sets with PandasWho This Book Is ForData Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers.
Practical Python Data Wrangling and Data Quality: Getting Started with Reading, Cleaning, and Analyzing Data
by Susan E. McGregorThe world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data.Use Python 3.8+ to read, write, and transform data from a variety of sourcesUnderstand and use programming basics in Python to wrangle data at scaleOrganize, document, and structure your code using best practicesCollect data from structured data files, web pages, and APIsPerform basic statistical analyses to make meaning from datasetsVisualize and present data in clear and compelling ways
Practical Python Programming for IoT: Build advanced IoT projects using a Raspberry Pi 4, MQTT, RESTful APIs, WebSockets, and Python 3
by Gary SmartLeverage Python and Raspberry Pi to create complex IoT applications capable of creating and detecting movement and measuring distance, light, and a host of other environmental conditionsKey FeaturesLearn the fundamentals of electronics and how to integrate them with a Raspberry PiUnderstand how to build RESTful APIs, WebSocket APIs, and MQTT-based applicationsExplore alternative approaches to structuring IoT applications with PythonBook DescriptionThe age of connected devices is here, be it fitness bands or smart homes. It's now more important than ever to understand how hardware components interact with the internet to collect and analyze user data. The Internet of Things (IoT), combined with the popular open source language Python, can be used to build powerful and intelligent IoT systems with intuitive interfaces. This book consists of three parts, with the first focusing on the "Internet" component of IoT. You'll get to grips with end-to-end IoT app development to control an LED over the internet, before learning how to build RESTful APIs, WebSocket APIs, and MQTT services in Python. The second part delves into the fundamentals behind electronics and GPIO interfacing. As you progress to the last part, you'll focus on the "Things" aspect of IoT, where you will learn how to connect and control a range of electronic sensors and actuators using Python. You'll also explore a variety of topics, such as motor control, ultrasonic sensors, and temperature measurement. Finally, you'll get up to speed with advanced IoT programming techniques in Python, integrate with IoT visualization and automation platforms, and build a comprehensive IoT project. By the end of this book, you'll be well-versed with IoT development and have the knowledge you need to build sophisticated IoT systems using Python.What you will learnUnderstand electronic interfacing with Raspberry Pi from scratchGain knowledge of building sensor and actuator electronic circuitsStructure your code in Python using Async IO, pub/sub models, and moreAutomate real-world IoT projects using sensor and actuator integrationIntegrate electronics with ThingSpeak and IFTTT to enable automationBuild and use RESTful APIs, WebSockets, and MQTT with sensors and actuatorsSet up a Raspberry Pi and Python development environment for IoT projectsWho this book is forThis IoT Python book is for application developers, IoT professionals, or anyone interested in building IoT applications using the Python programming language. It will also be particularly helpful for mid to senior-level software engineers who are experienced in desktop, web, and mobile development, but have little to no experience of electronics, physical computing, and IoT.
Practical Quantum Computing for Developers: Programming Quantum Rigs In The Cloud Using Python, Quantum Assembly Language And Ibm Qexperience
by Vladimir SilvaWrite algorithms and program in the new field of quantum computing. This book covers major topics such as the physical components of a quantum computer: qubits, entanglement, logic gates, circuits, and how they differ from a traditional computer. Also, Practical Quantum Computing for Developers discusses quantum computing in the cloud using IBM Q Experience including: the composer, quantum scores, experiments, circuits, simulators, real quantum devices, and more. You’ll be able to run experiments in the cloud on a real quantum device.Furthermore, this book shows you how to do quantum programming using the QISKit (Quantum Information Software Kit), Python SDK, and other APIs such as QASM (Quantum Assembly). You’ll learn to write code using these languages and execute it against simulators (local or remote) or a real quantum computer provided by IBM’s Q Experience. Finally, you’ll learn the current quantum algorithms for entanglement, random number generation, linear search, integer factorization, and others. You’ll peak inside the inner workings of the Bell states for entanglement, Grover’s algorithm for linear search, Shor’s algorithm for integer factorization, and other algorithms in the fields of optimization, and more.Along the way you’ll also cover game theory with the Magic Square, an example of quantum pseudo-telepathy where parties sharing entangled states can be observed to have some kind of communication between them. In this game Alice and Bob play against a referee. Quantum mechanics allows Alice and Bob to always win!By the end of this book, you will understand how this emerging technology provides massive parallelism and significant computational speedups over classical computers, and will be prepared to program quantum computers which are expected to replace traditional computers in the data center.What You Will LearnUse the Q Experience Composer, the first-of-its-kind web console to create visual programs/experiments and submit them to a quantum simulator or real device on the cloudRun programs remotely using the Q Experience REST API Write algorithms that provide superior performance over their classical counterpartsBuild a Node.js REST client for authenticating, listing remote devices, querying information about quantum processors, and listing or running experiments remotely in the cloudCreate a quantum number generator: The quintessential coin flip with a quantum twistDiscover quantum teleportation: This algorithm demonstrates how the exact state of a qubit (quantum information) can be transmitted from one location to another, with the help of classical communication and quantum entanglement between the sender and receiverPeek into single qubit operations with the classic game of Battleships with a quantum twistHandle the counterfeit coin problem: a classic puzzle that consists of finding a counterfeit coin in a beam balance among eight coins in only two turnsWho This Book Is ForDevelopers and programmers interested in this new field of computing.
Practical R 4: Applying R to Data Manipulation, Processing and Integration
by Jon WestfallGet started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio. Utilizing many examples and projects, this book teaches you how to get data into R and how to work with that data using R. Once grounded in the fundamentals, the rest of Practical R 4 dives into specific projects and examples starting with running and analyzing a survey using R and LimeSurvey. Next, you'll carry out advanced statistical analysis using R and MouselabWeb. Then, you’ll see how R can work for you without statistics, including how R can be used to automate data formatting, manipulation, reporting, and custom functions. The final part of this book discusses using R on a server; you’ll build a script with R that can run an RStudio Server and monitor a report source for changes to alert the user when something has changed. This project includes both regular email alerting and push notification. And, finally, you’ll use R to create a customized daily rundown report of a person's most important information such as a weather report, daily calendar, to-do's and more. This demonstrates how to automate such a process so that every morning, the user navigates to the same web page and gets the updated report.What You Will Learn Set up and run an R script, including installation on a new machine and downloading and configuring R Turn any machine into a powerful data analytics platform accessible from anywhere with RStudio Server Write basic R scripts and modify existing scripts to suit your own needs Create basic HTML reports in R, inserting information as neededBuild a basic R package and distribute it Who This Book Is For Some prior exposure to statistics, programming, and maybe SAS is recommended but not required.
Practical RDF: Solving Problems with the Resource Description Framework
by Shelley PowersThe Resource Description Framework (RDF) is a structure for describing and interchanging metadata on the Web--anything from library catalogs and worldwide directories to bioinformatics, Mozilla internal data structures, and knowledge bases for artificial intelligence projects. RDF provides a consistent framework and syntax for describing and querying data, making it possible to share website descriptions more easily. RDF's capabilities, however, have long been shrouded by its reputation for complexity and a difficult family of specifications. Practical RDF breaks through this reputation with immediate and solvable problems to help you understand, master, and implement RDF solutions.Practical RDF explains RDF from the ground up, providing real-world examples and descriptions of how the technology is being used in applications like Mozilla, FOAF, and Chandler, as well as infrastructure you can use to build your own applications. This book cuts to the heart of the W3C's often obscure specifications, giving you tools to apply RDF successfully in your own projects.The first part of the book focuses on the RDF specifications. After an introduction to RDF, the book covers the RDF specification documents themselves, including RDF Semantics and Concepts and Abstract Model specifications, RDF constructs, and the RDF Schema. The second section focuses on programming language support, and the tools and utilities that allow developers to review, edit, parse, store, and manipulate RDF/XML. Subsequent sections focus on RDF's data roots, programming and framework support, and practical implementation and use of RDF and RDF/XML.If you want to know how to apply RDF to information processing, Practical RDF is for you. Whether your interests lie in large-scale information aggregation and analysis or in smaller-scale projects like weblog syndication, this book will provide you with a solid foundation for working with RDF.
Practical React Native: Build Two Full Projects and One Full Game using React Native
by Frank ZammettiDiscover how to use React Native in the real world, from scratch. This book shows you what React Native has to offer, where it came from, and where it’s going. You'll begin with a solid foundation of practical knowledge, and then build on it immediately by constructing three different apps. You'll learn how to use each feature of React Native by working on two full projects and one full game. These aren’t just simple React Native Hello World examples (although you’ll naturally start there!) but are apps that you can, if you so choose, install on your mobile devices and use for real. Throughout this book, you'll gain real-world familiarity with React Native as well as supporting components from Expo, NativeBase, React Navigation and the Redux and Lodash libraries. You'll also build server-side code for a mobile React Native app to talk to using the popular Node.js and Socket.io library, providing you a holistic view of things even beyond React Native. And, you'll see many helpful tips, tricks and gotchas to watch out for along the way!Practical React Native offers practical exercises that will give you a solid grasp of building apps with React Native, allowing you to springboard into creating more advanced apps on your own.Creating a game with React Native will allow you to see a whole other perspective on what React Native can do.What You'll Learn Master the basics of React NativeCreate a logically structured projectReview interface elements, such as widgets, controls, and extensionsBuild layoutsWork with Expo, an open source toolchain Who This book Is ForThe primary audience is mobile developers and anyone looking to build for multiple mobile platforms and trying to do so with a codebase that is largely the same across all. Readers will need a decent foundation, but not necessarily be experts in, HTML, CSS, and JavaScript, but I'll assume little beyond that.
Practical Real-time Data Processing and Analytics
by Shilpi Saxena Saurabh GuptaA practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book • Learn about the various challenges in real-time data processing and use the right tools to overcome them • This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems • A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn • Get an introduction to the established real-time stack • Understand the key integration of all the components • Get a thorough understanding of the basic building blocks for real-time solution designing • Garnish the search and visualization aspects for your real-time solution • Get conceptually and practically acquainted with real-time analytics • Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.
Practical Recommender Systems
by Kim FalkSummaryOnline recommender systems help users find movies, jobs, restaurants-even romance! There's an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application!Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyRecommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors.About the BookPractical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you'll encounter as your site grows.What's insideHow to collect and understand user behaviorCollaborative and content-based filteringMachine learning algorithms Real-world examples in PythonAbout the ReaderReaders need intermediate programming and database skills.About the AuthorKim Falk is an experienced data scientist who works daily with machine learning and recommender systems.Table of ContentsPART 1 - GETTING READY FOR RECOMMENDER SYSTEMSWhat is a recommender? User behavior and how to collect it Monitoring the system Ratings and how to calculate themNon-personalized recommendationsThe user (and content) who came in from the coldPART 2 - RECOMMENDER ALGORITHMSFinding similarities among users and among contentCollaborative filtering in the neighborhoodEvaluating and testing your recommenderContent-based filteringFinding hidden genres with matrix factorizationTaking the best of all algorithms: implementing hybrid recommendersRanking and learning to rankFuture of recommender systems
Practical Reinforcement Learning
by Dr Engr. AkhtarMaster different reinforcement learning techniques and their practical implementation using OpenAI Gym, Python and Java About This Book • Take your machine learning skills to the next level with reinforcement learning techniques • Build automated decision-making capabilities in your systems • Cover Reinforcement Learning concepts, frameworks, algorithms, and more in detail Who This Book Is For Machine learning/AI practitioners, data scientists, data analysts, machine learning engineers, and developers who are looking to expand their existing knowledge to build optimized machine learning models, will find this book very useful. What You Will Learn • Understand the basics of reinforcement learning methods, algorithms, and more, and the differences between supervised, unsupervised, and reinforcement learning • Master the Markov Decision Process math framework by building an OO-MDP Domain in Java • Learn dynamic programming principles and the implementation of Fibonacci computation in Java • Understand Python implementation of temporal difference learning • Develop Monte Carlo methods and various policies used to build a Monte Carlo simulator using Python • Understand Policy Gradient methods and policies applied in the reinforcement domain • Instill reinforcement methods in the autonomous platform using a moving car example • Apply reinforcement learning algorithms in games with REINFORCEjs In Detail Reinforcement learning (RL) is becoming a popular tool for constructing autonomous systems that can improve themselves with experience. We will break the RL framework into its core building blocks, and provide you with details of each element. This book aims to strengthen your machine learning skills by acquainting you with reinforcement learning algorithms and techniques. This book is divided into three parts. The first part defines Reinforcement Learning and describes its basics. It also covers the basics of Python and Java frameworks, which we are going to use later in the book. The second part discusses learning techniques with basic algorithms such as Temporal Difference, Monte Carlo, and Policy Gradient—all with practical examples. Lastly, in the third part we apply Reinforcement Learning with the most recent and widely used algorithms via practical applications. By the end of this book, you'll know the practical implementation of case studies and current research activities to help you advance further with Reinforcement Learning. Style and approach This hands-on book will further expand your machine learning skills by teaching you the different reinforcement learning algorithms and techniques using practical examples.