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Practical Site Reliability Engineering
by Pethuru Raj Saravanan Pitchaimani Babu JayarajThis book will be a learning guide to help software developers, IT operational guys, DevOps engineers, performance specialists, and system engineers to understand how the emerging domain of SRE comes handy in automating and accelerating the process of designing, developing, debugging, deploying and delivering highly reliable applications and services.
Practical Sitecore 8 Configuration and Strategy: A User Guide for Sitecore's Content and Marketing Capabilities
by Phillip WicklundSitecore was recently recognized as one of the most reputable/reliable web content management solutions (WCMS) in the marketplace. Thousands of companies use Sitecore to help manage their web and mobile digital properties. Sitecore is a very large, complex platform that performs many robust functions and capabilities.As such, marketers and end users often have a hard time coming up to speed on the technology. Practical Sitecore 8 Configuration and Strategy: A User Guide for Sitecore's Content and Marketing Capabilities provides that opportunity. The flow of the book will take newbies step-by-step on how to configure Sitecore content, personalization, and marketing automation capabilities. Sprinkled in through the book will be callouts that highlight strategies and best practices—taking the book beyond just the “how to” step-by-step procedures that can be found elsewhere. Practical Sitecore 8 Configuration and Strategy:Brings you up to speed on Sitecore without requiring a training class.Provides the information in a clear, logical outline that takes users from simple, foundational concepts to more advanced concepts at the end.Rounds out existing sources of documentation with strategies and best practices from real-world experience.What You'll LearnHow to manage content in SitecoreHow to create web forms and landing pagesHow to optimize the site through personalization and A/B/N testingHow to use Sitecore for your marketing campaignsHow to leverage analytics for custom measurement/engagement strategiesHow to create a robust governance plan for your Sitecore propertiesWho This Book Is ForThe key target audience for this book are content administrators (content authoring, forms development, etc.) and digital marketers (campaigns, analytics, marketing automation, experience optimization, etc.) using the Sitecore platform.
Practical Smart Device Design and Construction: Understanding Smart Technologies and How to Build Them Yourself
by Christopher HarroldWith the rapid development of the Internet of Things, a gap has emerged in skills versus knowledge in an industry typically segmented into hardware versus software. Practitioners are now expected to possess capabilities across the spectrum of hardware and software skills to create these smart devices.This book explores these skill sets in an instructive way, beginning at the foundations of what makes “smart” technology smart, addressing the basics of hardware and hardware design, software, user experiences, and culminating in the considerations and means of building a fully formed smart device, capable of being used in a commercial capacity, versus a DIY project. Practical Smart Device Design and Construction includes a set of starter projects designed to encourage the novice to build and learn from doing. Each project also includes a summary guiding you where to go next, and how to tie the practical, hands-on experience together with what they have learned to take the next step on their own.What You'll LearnPractical smart device design and construction considerations such as size, power consumption, wiring needs, analog vs digital, and sensor types and usesMethods and tools for creating their own designs such as circuit board designs; and wiring and prototyping toolsHands-on guidance through their own prototype projects and building it alongside the projects in this bookSoftware considerations for speed versus ease, security, and basics of programming and data analytics for smart devicesWho This Book Is ForThose with some technical skills, or at least a familiarity with technical topics, who are looking for the means and skills to start experimenting with combined hardware and software projects in order to gain familiarity and comfort with the smart device space.
Practical Smoothing: The Joys of P-splines
by Brian D. Marx Paul H.C. EilersThis is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with simple, discrete, roughness penalties. They were introduced by the authors in 1996 and have been used in many diverse applications. The regression basis makes it straightforward to handle non-normal data, like in generalized linear models. The authors demonstrate optimal smoothing, using mixed model technology and Bayesian estimation, in addition to classical tools like cross-validation and AIC, covering theory and applications with code in R. Going far beyond simple smoothing, they also show how to use P-splines for regression on signals, varying-coefficient models, quantile and expectile smoothing, and composite links for grouped data. Penalties are the crucial elements of P-splines; with proper modifications they can handle periodic and circular data as well as shape constraints. Combining penalties with tensor products of B-splines extends these attractive properties to multiple dimensions. An appendix offers a systematic comparison to other smoothers.
Practical Social Engineering: A Primer for the Ethical Hacker
by Joe GrayA guide to hacking the human element.Even the most advanced security teams can do little to defend against an employee clicking a malicious link, opening an email attachment, or revealing sensitive information in a phone call. Practical Social Engineering will help you better understand the techniques behind these social engineering attacks and how to thwart cyber criminals and malicious actors who use them to take advantage of human nature.Joe Gray, an award-winning expert on social engineering, shares case studies, best practices, open source intelligence (OSINT) tools, and templates for orchestrating and reporting attacks so companies can better protect themselves. He outlines creative techniques to trick users out of their credentials, such as leveraging Python scripts and editing HTML files to clone a legitimate website. Once you&’ve succeeded in harvesting information about your targets with advanced OSINT methods, you&’ll discover how to defend your own organization from similar threats. You&’ll learn how to: Apply phishing techniques like spoofing, squatting, and standing up your own web server to avoid detection Use OSINT tools like Recon-ng, theHarvester, and Hunter Capture a target&’s information from social media Collect and report metrics about the success of your attack Implement technical controls and awareness programs to help defend against social engineering Fast-paced, hands-on, and ethically focused, Practical Social Engineering is a book every pentester can put to use immediately.
Practical Social Network Analysis with Python (Computer Communications and Networks)
by K. G. Srinivasa Krishna Raj P.M. Ankith MohanThis book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis.With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks.This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
Practical Software Development Techniques
by Edward CrookshanksThis book provides an overview of tools and techniques used in enterprise software development, many of which are not taught in academic programs or learned on the job. This is an ideal resource containing lots of practical information and code examples that you need to master as a member of an enterprise development team. This book aggregates many of these "on the job" tools and techniques into a concise format and presents them as both discussion topics and with code examples. The reader will not only get an overview of these tools and techniques, but also several discussions concerning operational aspects of enterprise software development and how it differs from smaller development efforts. For example, in the chapter on Design Patterns and Architecture, the author describes the basics of design patterns but only highlights those that are more important in enterprise applications due to separation of duties, enterprise security, etc. The architecture discussion revolves has a similar emphasis - different teams may manage different aspects of the application''s components with little or no access to the developer. This aspect of restricted access is also mentioned in the section on logging. Theory of logging and discussions of what to log are briefly mentioned, the configuration of the logging tools is demonstrated along with a discussion of why it''s very important in an enterprise environment. What you''ll learn Version control in a team environment Debugging, logging, and refactoring Unit testing, build tools, continuous integration An overview of business and functional requirements Enterprise design patterns and architecture Who this book is for Student and software developers who are new to enterprise environments and recent graduates who want to convert their academic experience into real-world skills. It is assumed that the reader is familiar with Java, . NET, C++ or another high-level programming language. The reader should also be familiar with the differences between console applications, GUI applications and service/daemon applications. Table of Contents 1: Version Control 2: Unit Testing and Test Driven Development 3: Refactoring 4: Build Tools and Continuous Integration 5: Debugging 6: Development Methodologies and SDLC 7: Design Patterns and Architecture 8: Software Requirements 9: Just Enough SQL Appendix A: Enterprise Considerations and Other Topics Appendix B: Discussion Questions Appendix C: Database details Appendix D: Bibliography
Practical Solutions for Diverse Real-World NLP Applications (Signals and Communication Technology)
by Mourad AbbasThis book unveils the most advanced techniques and innovative applications in the natural language processing (NLP) field. It uncovers the secrets to enhancing language understanding, and presents practical solutions to different NLP tasks, as text augmentation, paraphrase generation, and restoring spaces and punctuation in multiple languages. It unlocks the potential of hierarchical multi-task learning for cross-lingual phoneme recognition, and allows readers to explore more real-world applications such as error correction, aggregating industrial security findings as well as predicting music emotion values from social media conversations. "Practical Solutions for Diverse Real-World NLP Applications" is the suitable guidebook for researchers, students, and practitioners as it paves the way for them by delivering invaluable insights and knowledge.
Practical Speech User Interface Design (Human Factors and Ergonomics)
by James R. LewisAlthough speech is the most natural form of communication between humans, most people find using speech to communicate with machines anything but natural. Drawing from psychology, human-computer interaction, linguistics, and communication theory, Practical Speech User Interface Design provides a comprehensive yet concise survey of practical speech
Practical Splunk Search Processing Language: A Guide for Mastering SPL Commands for Maximum Efficiency and Outcome
by Karun SubramanianUse this practical guide to the Splunk operational data intelligence platform to search, visualize, and analyze petabyte-scale, unstructured machine data. Get to the heart of the platform and use the Search Processing Language (SPL) tool to query the platform to find the answers you need. With more than 140 commands, SPL gives you the power to ask any question of machine data. However, many users (both newbies and experienced users) find the language difficult to grasp and complex. This book takes you through the basics of SPL using plenty of hands-on examples and emphasizes the most impactful SPL commands (such as eval, stats, and timechart). You will understand the most efficient ways to query Splunk (such as learning the drawbacks of subsearches and join, and why it makes sense to use tstats). You will be introduced to lesser-known commands that can be very useful, such as using the command rex to extract fields and erex to generate regular expressions automatically. In addition, you will learn how to create basic visualizations (such as charts and tables) and use prescriptive guidance on search optimization. For those ready to take it to the next level, the author introduces advanced commands such as predict, kmeans, and cluster.What You Will LearnUse real-world scenarios (such as analyzing a web access log) to search, group, correlate, and create reports using SPL commandsEnhance your search results using lookups and create new lookup tables using SPL commandsExtract fields from your search results Compare data from multiple time frames in one chart (such as comparing your current day application performance to the average of the past 30 days) Analyze the performance of your search using Job Inspector and identify execution costs of various components of your search Who This Book Is ForApplication developers, architects, DevOps engineers, application support engineers, network operations center analysts, security operations center (SOC) analysts, and cyber security professionals who use Splunk to search and analyze their machine data
Practical Spring Cloud Function: Developing Cloud-Native Functions for Multi-Cloud and Hybrid-Cloud Environments
by Banu ParasuramanUnlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements. Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI). After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently. What You Will LearnWrite functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShiftSet up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and othersBuild, test, and deploy a simple example with Spring Cloud FunctionDevelop an event-driven data pipeline with Spring Cloud FunctionIntegrate with AI and machine learning modelsApply Spring Cloud Function to the Internet of Things (IoT)Get industry-specific examples of Spring Cloud Function in actionWho This Book Is For Software and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well.
Practical Spring LDAP
by Balaji VaranasiPractical Spring LDAP is your guide to developing Java-based enterprise applications using the Spring LDAP Framework. This book explains the purpose and fundamental concepts of LDAP before giving a comprehensive tour of the latest version, Spring LDAP 1. 3. 2. It provides a detailed treatment of LDAP controls and the new features of Spring LDAP 1. 3. 2 such as Object Directory Mapping and LDIF parsing. LDAP has become the de-facto standard for storing and accessing information in enterprises. Despite its widespread adoption, developers often struggle when it comes to using this technology effectively. The traditional JNDI approach has proven to be painful and has resulted in complex, less modular applications. The Spring LDAP Framework provides an ideal alternative.
Practical Spring LDAP: Using Enterprise Java-Based LDAP in Spring Data and Spring Framework 6
by Balaji Varanasi Andres SaccoThis revised edition is your practical, hands-on guide to developing Java-based enterprise applications with big data or batches of data using the Spring LDAP and the Spring Data LDAP frameworks. The book covers these popular Spring project modules and explains the purpose and fundamental concepts of LDAP before giving a comprehensive tour of the latest version of Spring LDAP and Spring Data LDAP as found in Spring Framework 6. The book provides a detailed treatment of LDAP controls and the new features of Spring LDAP such as Object Directory Mapping and LDIF parsing. LDAP has become the de facto standard for storing and accessing information in enterprises. Despite its widespread adoption, developers often struggle when it comes to using this technology effectively. The traditional Java LDAP and JNDI approaches have proven to be painful and have resulted in complex, less modular applications. The Spring LDAP framework provides an ideal alternative.After reading and using this book, you'll come away with a level of comfort for working with large batches of data or big data in your enterprise Spring applications development.What You'll LearnExplore "What is Java LDAP?" and understand the Spring LDAP and Spring Data LDAP frameworksSearch LDAP resourcesSort and page your LDAP resultsDive into object directory mappingHandle LDAP transactions and moreWho This Book Is ForIntermediate to advanced Java and Spring software developers; programmers with at least some prior experience in Java, especially the Spring Framework
Practical Statistical Learning and Data Science Methods: Case Studies from LISA 2020 Global Network, USA (STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health)
by O. Olawale Awe Eric A. VanceThis contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science. Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike. The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as “stat labs.” These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers.
Practical Statistics for Data Scientists: 50 Essential Concepts
by Peter Bruce Andrew BruceStatistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you’ll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that “learn” from dataUnsupervised learning methods for extracting meaning from unlabeled data
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
by Peter Bruce Andrew Bruce Peter GedeckStatistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you’ll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data
Practical Studies in E-Government
by Saïd Assar Imed Boughzala Isabelle BoydensInformation and communication technology (ICT) is permeating all aspects of service management; in the public sector, ICT is improving the capacity of government agencies to provide a wide array of innovative services that benefit citizens. E-Government is emerging as a multidisciplinary field of research based initially on empirical insights from practice. Efforts to theoretically anchor the field have opened perspectives from multiple research domains, as demonstrated in Practical Studies in E-Government. In this volume, the editors and contributors consider the evolution of the e-government field from both practical and research perspectives. Featuring in-depth case studies of initiatives in eight countries, the book deals with such technology-oriented issues as interoperability, prototyping, data quality, and advanced interfaces, and management-oriented issues as e-procurement, e-identification, election results verification, and information privacy. The book features best practices, tools for measuring and improving performance, and analytical methods for researchers.
Practical Svelte: Create Performant Applications with the Svelte Component Framework
by Alex LibbyLearn to leverage the power of Svelte to produce web applications that are efficient and fast. This project-oriented book simplifies creating sites using Svelte from start to finish, with little more than a text editor and familiar languages such as HTML, CSS, and JavaScript. It equips you with a starting toolset that you can use to develop future projects, incorporate into your existing workflow, and allow you to take your websites to the next level.Practical Svelte is an excellent resource for getting acquainted with creating and manipulating websites or online applications using a component framework approach. It takes the view that we don’t have to create something complex and unwieldy. We can build something quickly, using less code than some of its competitors, and extend it using the power of the API and plugins over time, without sacrificing speed or features. You will learn how to use the Svelte framework to rapidly create and deploy websites or online applications that are performant, with the minimum of fuss and using existing tools already available in the browser, get up to speed with individual features of the Svelte framework, and work through a series of small projects that will combine to produce a finished site at the end of the book – this to help consolidate skills from day one and create something that you can use as a basis for future projects. What You Will Learn Understand why Svelte’s popularity makes it the go-to framework for constructing applicationsLearn how to scaffold and implement web sites or online applications using SvelteCreate reusable components using Svelte that are interoperable with other frameworks and can solve real-world problemsPerform automated testing and deployment using tools such as CI/CD testing Work through some mini projects from start to finish, understanding what we can achieve using Svelte and where we may need to bring other tools into play Who This Book Is For Website developers who are already familiar with JavaScript, CSS, and HTML and are keen to learn how to leverage the Svelte component framework to quickly create web sites or online applications with little more than a text editor. It’s perfect for development teams who do not want to follow the mold and use a credible alternative to React or Angular.
Practical Swift
by Eric DowneyTake a firsthand tour of Xcode and all the latest features Swift 3 has to offer. If you have picked up this book, chances are you know a little bit about Swift Programming. With Practical Swift you'll develop an advanced understanding of the language that will enable you to create a reference guide using Xcode Playgrounds, one you can continue to grow throughout your iOS career. This book not only shows you how to code in a clean and concise manner, but also the why behind the code. Understanding why will be instrumental in your advancement as a Swift developer. What You'll learn: Review the evolution of Swift and the latest features in Swift 3 Study architecture and design patterns Examine Protocol Oriented Programming Understand Swift generics Test Swift code Build an iOS App with core data from scratch Who This Book Is For: The primary audience for this book is developers who have started learning iOS and Swift and want to learn more of the intermediate to advanced topics available in Swift. The secondary audience is developers who have experience in iOS and Swift and want a good reference book for concepts they might already know, but are looking to re-enforce.
Practical Synthetic Data Generation: Balancing Privacy and the Broad Availability of Data
by Khaled El Emam Lucy Mosquera Richard HoptroffBuilding and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data—fake data generated from real data—so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue.Data scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. Analysts will learn the principles and steps for generating synthetic data from real datasets. And business leaders will see how synthetic data can help accelerate time to a product or solution.This book describes:Steps for generating synthetic data using multivariate normal distributionsMethods for distribution fitting covering different goodness-of-fit metricsHow to replicate the simple structure of original dataAn approach for modeling data structure to consider complex relationshipsMultiple approaches and metrics you can use to assess data utilityHow analysis performed on real data can be replicated with synthetic dataPrivacy implications of synthetic data and methods to assess identity disclosure
Practical System Programming with C: Pragmatic Example Applications in Linux and Unix-Based Operating Systems
by Sri Manikanta PalakolluThis book teaches system programming with the latest versions of C through a set of practical examples and problems. It covers the development of a handful of programs, implementing efficient coding examples. Practical System Programming with C contains three main parts: getting your hands dirty with multithreaded C programming; practical system programming using concepts such as processes, signals, and inter-process communication; and advanced socket-based programming which consists of developing a network application for reliable communication. You will be introduced to a marvelous ecosystem of system programming with C, from handling basic system utility commands to communicating through socket programming. With the help of socket programming you will be able to build client-server applications in no time. The “secret sauce” of this book is its curated list of topics and solutions, which fit together through a set of different pragmatic examples; each topic is covered from scratch in an easy-to-learn way. On that journey, you’ll focus on practical implementations and an outline of best practices and potential pitfalls. The book also includes a bonus chapter with a list of advanced topics and directions to grow your skills. What You Will Learn Program with operating systems using the latest version of C Work with Linux Carry out multithreading with C Examine the POSIX standardsWork with files, directories, processes, and signals Explore IPC and how to work with it Who This Book Is For Programmers who have an exposure to C programming and want to learn system programming. This book will help them to learn about core concepts of operating systems with the help of C programming. .
Practical System programming for Rust developers: Build Fast And Secure Software For Linux/unix Systems With The Help Of Practical Examples
by Prabhu EshwarlaThis book is for developers with basic knowledge of Rust but little to no knowledge or experience of systems programming. System programmers who want to consider Rust as an alternative to C or C++ will also find this book useful.
Practical TLA+: Planning Driven Development
by Hillel WayneLearn how to design complex, correct programs and fix problems before writing a single line of code. This book is a practical, comprehensive resource on TLA+ programming with rich, complex examples. Practical TLA+ shows you how to use TLA+ to specify a complex system and test the design itself for bugs. You’ll learn how even a short TLA+ spec can find critical bugs. Start by getting your feet wet with an example of TLA+ used in a bank transfer system, to see how it helps you design, test, and build a better application. Then, get some fundamentals of TLA+ operators, logic, functions, PlusCal, models, and concurrency. Along the way you will discover how to organize your blueprints and how to specify distributed systems and eventual consistency. Finally, you’ll put what you learn into practice with some working case study applications, applying TLA+ to a wide variety of practical problems: from algorithm performance and data structures to business code and MapReduce. After reading and using this book, you'll have what you need to get started with TLA+ and how to use it in your mission-critical applications. What You'll LearnRead and write TLA+ specsCheck specs for broken invariants, race conditions, and liveness bugsDesign concurrency and distributed systemsLearn how TLA+ can help you with your day-to-day production workWho This Book Is ForThose with programming experience who are new to design and to TLA+.
Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master
by Ryan SleeperWhether you have some experience with Tableau software or are just getting started, this manual goes beyond the basics to help you build compelling, interactive data visualization applications. Author Ryan Sleeper, one of the worldâ??s most qualified Tableau consultants, complements his web posts and instructional videos with this guide to give you a firm understanding of how to use Tableau to find valuable insights in data.Over five sections, Sleeperâ??recognized as a Tableau Zen Master, Tableau Public Visualization of the Year author, and Tableau Iron Viz Championâ??provides visualization tips, tutorials, and strategies to help you avoid the pitfalls and take your Tableau knowledge to the next level.Practical Tableau sections include:Fundamentals: get started with Tableau from the beginningChart types: use step-by-step tutorials to build a variety of charts in TableauTips and tricks: learn innovative uses of parameters, color theory, how to make your Tableau workbooks run efficiently, and moreFramework: explore the INSIGHT framework, a proprietary process for building Tableau dashboardsStorytelling: learn tangible tactics for storytelling with data, including specific and actionable tips you can implement immediately
Practical TensorFlow.js: Deep Learning in Web App Development
by Juan De RiveraDevelop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web apps.The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis.Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js.What You'll LearnBuild deep learning products suitable for web browsersWork with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN)Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysisWho This Book Is For Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.