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Practical SQL: A Beginner's Guide to Storytelling with Data
by Anthony DeBarrosPractical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools. You’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently. You’ll learn how to: -Create databases and related tables using your own data -Define the right data types for your information -Aggregate, sort, and filter data to find patterns -Use basic math and advanced statistical functions -Identify errors in data and clean them up -Import and export data using delimited text files -Write queries for geographic information systems (GIS) -Create advanced queries and automate tasks Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.
Practical SQL, 2nd Edition: A Beginner's Guide to Storytelling with Data
by Anthony DeBarrosAnalyze data like a pro, even if you&’re a beginner.Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. Anthony DeBarros, a journalist and data analyst, focuses on using SQL to find the story within your data. The examples and code use the open-source database PostgreSQL and its companion pgAdmin interface, and the concepts you learn will apply to most database management systems, including MySQL, Oracle, SQLite, and others.*You&’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from real-world datasets such as US Census demographics, New York City taxi rides, and earthquakes from US Geological Survey. Each chapter includes exercises and examples that teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.You&’ll learn how to: • Create databases and related tables using your own data • Aggregate, sort, and filter data to find patterns • Use functions for basic math and advanced statistical operations • Identify errors in data and clean them up • Analyze spatial data with a geographic information system (PostGIS) • Create advanced queries and automate tasksThis updated second edition has been thoroughly revised to reflect the latest in SQL features, including additional advanced query techniques for wrangling data. This edition also has two new chapters: an expanded set of instructions on for setting up your system plus a chapter on using PostgreSQL with the popular JSON data interchange format. Learning SQL doesn&’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases.* Microsoft SQL Server employs a variant of the language called T-SQL, which is not covered by Practical SQL.
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 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 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 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.
Practical Test Automation: Learn to Use Jasmine, RSpec, and Cucumber Effectively for Your TDD and BDD
by Panos MatsinopoulosLearn the principles behind test-driven development (TDD) and behavior-driven development (BDD) and see how Jasmine, RSpec and Cucumber can be used to your advantage. This book examines some of the leading technologies used for testing. You'll see how to use Jasmine’s features to work with a JavaScript application. You will learn how to use Mini Test and RSpec with Ruby and Rubymine. Finally, you’ll use Cucumber to develop your software using a BDD approach. Understanding test automation is a vital skill for any web developer. Practical Test Automation breaks down for you some of the important TDD and BDD technologies on the modern web. What You'll Learn Test an example JavaScript application with JasmineUse Jasmine with JS BinWork with Minitest for test-driven developmentTest an example Ruby project with RSpecUse Cucumber and Gherkin for behavior-driven developmentIntegrate Cucumber with RSpec Who This Book Is For This book is for anyone who wants to learn test automation and more about test-driven development and behavior-driven development.
Practical Test-Driven Development using C# 7: Unleash The Power Of Tdd By Implementing Real World Examples Under . Net Environment And Javascript
by John CallawayTest-Driven Development (TDD) is a methodology that helps you to write as little as code as possible to satisfy the software requirements, and that what you've written does what its supposed to do. If you're looking for a practical resource on Test-Driven Development this is the book for you. You've found a practical end to end guide that will help you to implement Test-Driven Techniques for your software development projects.
Practical Test-Driven Development using C# 7: Unleash the power of TDD by implementing real world examples under .NET environment and JavaScript
by John Callaway Clayton HuntDevelop applications for the real world with a thorough software testing approach Key Features Develop a thorough understanding of TDD and how it can help you develop simpler applications with no defects using C# and JavaScript Adapt to the mindset of writing tests before code by incorporating business goals, code manageability, and other factors Make all your software units and modules pass tests by analyzing failed tests and refactoring code as and when required Book Description Test-Driven Development (TDD) is a methodology that helps you to write as little as code as possible to satisfy software requirements, and ensures that what you've written does what it's supposed to do. If you're looking for a practical resource on Test-Driven Development this is the book for you. You've found a practical end-to-end guide that will help you implement Test-Driven Techniques for your software development projects. You will learn from industry standard patterns and practices, and shift from a conventional approach to a modern and efficient software testing approach in C# and JavaScript. This book starts with the basics of TDD and the components of a simple unit test. Then we look at setting up the testing framework so that you can easily run your tests in your development environment. You will then see the importance of defining and testing boundaries, abstracting away third-party code (including the .NET Framework), and working with different types of test double such as spies, mocks, and fakes. Moving on, you will learn how to think like a TDD developer when it comes to application development. Next, you'll focus on writing tests for new/changing requirements and covering newly discovered bugs, along with how to test JavaScript applications and perform integration testing. You’ll also learn how to identify code that is inherently un-testable, and identify some of the major problems with legacy applications that weren’t written with testability in mind. By the end of the book, you’ll have all the TDD skills you'll need and you’ll be able to re-enter the world as a TDD expert! What you will learn The core concepts of TDD Testing in action with a real-world case study in C# and JavaScript using React Writing proper Unit Tests and testable code for your application Using different types of test double such as stubs, spies, and mocks Growing an application guided by tests Exploring new developments on a green-field application Mitigating the problems associated with writing tests for legacy applications Modifying a legacy application to make it testableWho this book is for This book is for software developers with a basic knowledge of Test Driven Development (TDD) who want a thorough understanding of how TDD can benefit them and the applications they produce. The examples in this book are in C#, and you will need a basic understanding of C# to work through these examples.
Practical Text Analytics: Maximizing the Value of Text Data (Advances in Analytics and Data Science #2)
by Murugan Anandarajan Chelsey Hill Thomas NolanThis book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.
Practical Text Analytics
by Steven StruhlBridging the gap between the marketer who must put text analytics to use and the increasingly rarefied community of data analysis experts, Practical Text Analytics is an accessible guide to the many remarkable advances in text analytics that specialists are discussing among themselves. Instead of being a resource for programmers, a book on theory or an introduction on how to use advanced statistical programs, this daily reference resource cuts through the profusion of jargon, evaluating the strengths and weaknesses of various methods and serving as a guide to what is credible in this fast-moving and often confusing field. Practical Text Analytics provides guidance on the application of text analytics for marketing professionals who must interpret the results and apply them in their campaigns. It presents the process of analysis in ways that people who use the data need to see them, helping marketers to clarify and organize confidently the confusing array of methods, frame the right questions and apply the results successfully to find meaning in any unstructured data and develop powerful new marketing strategies. About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations enabling marketers to gain confidence in applying the tools and techniques and in commissioning external research.
Practical Text Mining with Perl
by Roger BilisolyProvides readers with the methods, algorithms, and means to perform text mining tasksThis book is devoted to the fundamentals of text mining using Perl, an open-source programming tool that is freely available via the Internet (www.perl.org). It covers mining ideas from several perspectives--statistics, data mining, linguistics, and information retrieval--and provides readers with the means to successfully complete text mining tasks on their own.The book begins with an introduction to regular expressions, a text pattern methodology, and quantitative text summaries, all of which are fundamental tools of analyzing text. Then, it builds upon this foundation to explore:Probability and texts, including the bag-of-words modelInformation retrieval techniques such as the TF-IDF similarity measureConcordance lines and corpus linguisticsMultivariate techniques such as correlation, principal components analysis, and clusteringPerl modules, German, and permutation testsEach chapter is devoted to a single key topic, and the author carefully and thoughtfully introduces mathematical concepts as they arise, allowing readers to learn as they go without having to refer to additional books. The inclusion of numerous exercises and worked-out examples further complements the book's student-friendly format.Practical Text Mining with Perl is ideal as a textbook for undergraduate and graduate courses in text mining and as a reference for a variety of professionals who are interested in extracting information from text documents.
Practical Threat Detection Engineering: A hands-on guide to planning, developing, and validating detection capabilities
by null Megan Roddie null Jason Deyalsingh null Gary J. KatzGo on a journey through the threat detection engineering lifecycle while enriching your skill set and protecting your organizationKey FeaturesGain a comprehensive understanding of threat validationLeverage open-source tools to test security detectionsHarness open-source content to supplement detection and testingBook DescriptionThreat validation is an indispensable component of every security detection program, ensuring a healthy detection pipeline. This comprehensive detection engineering guide will serve as an introduction for those who are new to detection validation, providing valuable guidelines to swiftly bring you up to speed. The book will show you how to apply the supplied frameworks to assess, test, and validate your detection program. It covers the entire life cycle of a detection, from creation to validation, with the help of real-world examples. Featuring hands-on tutorials and projects, this guide will enable you to confidently validate the detections in your security program. This book serves as your guide to building a career in detection engineering, highlighting the essential skills and knowledge vital for detection engineers in today's landscape. By the end of this book, you’ll have developed the skills necessary to test your security detection program and strengthen your organization’s security measures.What you will learnUnderstand the detection engineering processBuild a detection engineering test labLearn how to maintain detections as codeUnderstand how threat intelligence can be used to drive detection developmentProve the effectiveness of detection capabilities to business leadershipLearn how to limit attackers' ability to inflict damage by detecting any malicious activity earlyWho this book is forThis book is for security analysts and engineers seeking to improve their organization’s security posture by mastering the detection engineering lifecycle. To get started with this book, you’ll need a basic understanding of cybersecurity concepts, along with some experience with detection and alert capabilities.
Practical Threat Intelligence and Data-Driven Threat Hunting: A hands-on guide to threat hunting with the ATT&CK™ Framework and open source tools
by Valentina Costa-GazconGet to grips with cyber threat intelligence and data-driven threat hunting while exploring expert tips and techniquesKey FeaturesSet up an environment to centralize all data in an Elasticsearch, Logstash, and Kibana (ELK) server that enables threat huntingCarry out atomic hunts to start the threat hunting process and understand the environmentPerform advanced hunting using MITRE ATT&CK Evals emulations and Mordor datasetsBook DescriptionThreat hunting (TH) provides cybersecurity analysts and enterprises with the opportunity to proactively defend themselves by getting ahead of threats before they can cause major damage to their business.This book is not only an introduction for those who don't know much about the cyber threat intelligence (CTI) and TH world, but also a guide for those with more advanced knowledge of other cybersecurity fields who are looking to implement a TH program from scratch.You will start by exploring what threat intelligence is and how it can be used to detect and prevent cyber threats. As you progress, you'll learn how to collect data, along with understanding it by developing data models. The book will also show you how to set up an environment for TH using open source tools. Later, you will focus on how to plan a hunt with practical examples, before going on to explore the MITRE ATT&CK framework.By the end of this book, you'll have the skills you need to be able to carry out effective hunts in your own environment.What you will learnUnderstand what CTI is, its key concepts, and how it is useful for preventing threats and protecting your organizationExplore the different stages of the TH processModel the data collected and understand how to document the findingsSimulate threat actor activity in a lab environmentUse the information collected to detect breaches and validate the results of your queriesUse documentation and strategies to communicate processes to senior management and the wider businessWho this book is forIf you are looking to start out in the cyber intelligence and threat hunting domains and want to know more about how to implement a threat hunting division with open-source tools, then this cyber threat intelligence book is for you.
Practical Time Series Analysis: Prediction with Statistics and Machine Learning
by Aileen NielsenTime series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase.Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly.You’ll get the guidance you need to confidently:Find and wrangle time series dataUndertake exploratory time series data analysisStore temporal dataSimulate time series dataGenerate and select features for a time seriesMeasure errorForecast and classify time series with machine or deep learningEvaluate accuracy and performance
Practical Time-Series Analysis
by Dr Pks Prakash Dr Avishek PalStep by Step guide filled with real world practical examples. About This Book • Get your first experience with data analysis with one of the most powerful types of analysis—time-series. • Find patterns in your data and predict the future pattern based on historical data. • Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn • Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project • Develop an understanding of loading, exploring, and visualizing time-series data • Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series • Take advantage of exponential smoothing to tackle noise in time series data • Learn how to use auto-regressive models to make predictions using time-series data • Build predictive models on time series using techniques based on auto-regressive moving averages • Discover recent advancements in deep learning to build accurate forecasting models for time series • Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.
Practical Tinker Board: Getting Started and Building Projects with the ASUS Single-Board Computer
by Liz ClarkGet started with the ASUS Tinker Board and begin building and expanding your own projects. This book covers the basic operating systems offered by ASUS for the Tinker Board and Tinker Board S, TinkerOS and Android, and then dives deeper into its capabilities for projects; such as a music streamer or a weather display with internet connectivity. Beginners will find the resources necessary to follow along and more seasoned makers can review additional information to engage with this new single-board computer platform. The projects are broad enough to show off the capability of the Tinker Board’s hardware and they can be used as is or you can add to them based on your skill level. The ASUS Tinker Board offers an increase in hardware specs and, as a result, is more powerful compared to other single-board computers on the market, making it a great option for projects that would have previously been a challenge to run on other boards, such as the Raspberry Pi. Single-board computers in general are also gaining in popularity as solutions for many DIY tech projects, ranging from gaming to file storage to being a small form factor desktop Linux computer. Practical Tinker Board is a great resource to the maker community, enabling people to begin truly exploring the Tinker Board. What You’ll Learn:Review ASUS Tinker Board's capabilities and functionsGain a deeper understanding of different Linux distributionsBuild useful projects with a range of hardware and softwareTake an in-depth look at how to install, configure and use ASUS Tinker Board in projectsWho This Book Is For:Those who have previously worked on some beginner maker projects, such as basic Arduino and Raspberry Pi projects, and are looking to expand their skills and knowledge of Linux, single board computers, programming and project builds.
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+.