Hands-On Machine Learning with Microsoft Excel 2019

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 178934512X
Total Pages : 243 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Machine Learning with Microsoft Excel 2019 by : Julio Cesar Rodriguez Martino

Download or read book Hands-On Machine Learning with Microsoft Excel 2019 written by Julio Cesar Rodriguez Martino and published by Packt Publishing Ltd. This book was released on 2019-04-30 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key FeaturesUse Microsoft's product Excel to build advanced forecasting models using varied examples Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more Derive data-driven techniques using Excel plugins and APIs without much code required Book Description We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learnUse Excel to preview and cleanse datasetsUnderstand correlations between variables and optimize the input to machine learning modelsUse and evaluate different machine learning models from ExcelUnderstand the use of different visualizationsLearn the basic concepts and calculations to understand how artificial neural networks workLearn how to connect Excel to the Microsoft Azure cloudGet beyond proof of concepts and build fully functional data analysis flowsWho this book is for This book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

Hands-On Financial Modeling with Microsoft Excel 2019

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1789531632
Total Pages : 280 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Hands-On Financial Modeling with Microsoft Excel 2019 by : Shmuel Oluwa

Download or read book Hands-On Financial Modeling with Microsoft Excel 2019 written by Shmuel Oluwa and published by Packt Publishing Ltd. This book was released on 2019-07-11 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key FeaturesA non data professionals guide to exploring Excel's financial functions and pivot tablesLearn to prepare various models for income and cash flow statements, and balance sheetsLearn to perform valuations and identify growth drivers with real-world case studiesBook Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components of Excel for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learnIdentify the growth drivers derived from processing historical data in ExcelUse discounted cash flow (DCF) for efficient investment analysisBuild a financial model by projecting balance sheets, profit, and lossApply a Monte Carlo simulation to derive key assumptions for your financial modelPrepare detailed asset and debt schedule models in ExcelDiscover the latest and advanced features of Excel 2019Calculate profitability ratios using various profit parametersWho this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel.

Learn Data Mining Through Excel

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Author :
Publisher : Apress
ISBN 13 : 1484259823
Total Pages : 223 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Learn Data Mining Through Excel by : Hong Zhou

Download or read book Learn Data Mining Through Excel written by Hong Zhou and published by Apress. This book was released on 2020-06-13 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help. Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages. This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. What You Will Learn Comprehend data mining using a visual step-by-step approachBuild on a theoretical introduction of a data mining method, followed by an Excel implementationUnveil the mystery behind machine learning algorithms, making a complex topic accessible to everyoneBecome skilled in creative uses of Excel formulas and functionsObtain hands-on experience with data mining and Excel Who This Book Is For Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended.

Microsoft Excel 2019 Data Analysis and Business Modeling

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Author :
Publisher : Microsoft Press
ISBN 13 : 1509306080
Total Pages : 1488 pages
Book Rating : 4.5/5 (93 download)

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Book Synopsis Microsoft Excel 2019 Data Analysis and Business Modeling by : Wayne Winston

Download or read book Microsoft Excel 2019 Data Analysis and Business Modeling written by Wayne Winston and published by Microsoft Press. This book was released on 2019-03-28 with total page 1488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros

Create Dynamic Charts in Microsoft Office Excel 2007 and Beyond

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Author :
Publisher : Pearson Education
ISBN 13 : 0735638187
Total Pages : 856 pages
Book Rating : 4.7/5 (356 download)

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Book Synopsis Create Dynamic Charts in Microsoft Office Excel 2007 and Beyond by : Reinhold Scheck

Download or read book Create Dynamic Charts in Microsoft Office Excel 2007 and Beyond written by Reinhold Scheck and published by Pearson Education. This book was released on 2008-12-10 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extend your Excel 2007 skills—and create more-powerful and compelling charts in less time. Guided by an Excel expert, you’ll learn how to turn flat, static charts into dynamic solutions—where you can visualize and manipulate data countless ways with a simple mouse click. Get the hands-on practice and examples you need to produce your own, professional-quality results. No programming required! Maximize the impact of your ideas and data! Learn how your design decisions affect perception and comprehension Match the right chart type to your communication objective Visualize—then build—your solution using the author’s five-step approach Apply the science of color to make the right things pop Add controls—such as drop-down lists and scroll bars—without coding Use conditional formatting to dynamically highlight and analyze data Unleash your chart-making creativity—and bring numbers to life! CD includes: More than 150 sample, customizable charts for various business scenarios Helpful worksheets and job aids Bonus content and resources Fully searchable eBook For customers who purchase an ebook version of this title, instructions for downloading the CD files can be found in the ebook.

Hands-On Data Science for Marketing

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 178934882X
Total Pages : 448 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Data Science for Marketing by : Yoon Hyup Hwang

Download or read book Hands-On Data Science for Marketing written by Yoon Hyup Hwang and published by Packt Publishing Ltd. This book was released on 2019-03-29 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimize your marketing strategies through analytics and machine learning Key FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learnLearn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segmentsWho this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.

Data Forecasting and Segmentation Using Microsoft Excel

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1803235268
Total Pages : 325 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Data Forecasting and Segmentation Using Microsoft Excel by : Fernando Roque

Download or read book Data Forecasting and Segmentation Using Microsoft Excel written by Fernando Roque and published by Packt Publishing Ltd. This book was released on 2022-05-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perform time series forecasts, linear prediction, and data segmentation with no-code Excel machine learning Key Features • Segment data, regression predictions, and time series forecasts without writing any code • Group multiple variables with K-means using Excel plugin without programming • Build, validate, and predict with a multiple linear regression model and time series forecasts Book Description Data Forecasting and Segmentation Using Microsoft Excel guides you through basic statistics to test whether your data can be used to perform regression predictions and time series forecasts. The exercises covered in this book use real-life data from Kaggle, such as demand for seasonal air tickets and credit card fraud detection. You'll learn how to apply the grouping K-means algorithm, which helps you find segments of your data that are impossible to see with other analyses, such as business intelligence (BI) and pivot analysis. By analyzing groups returned by K-means, you'll be able to detect outliers that could indicate possible fraud or a bad function in network packets. By the end of this Microsoft Excel book, you'll be able to use the classification algorithm to group data with different variables. You'll also be able to train linear and time series models to perform predictions and forecasts based on past data. What you will learn • Understand why machine learning is important for classifying data segmentation • Focus on basic statistics tests for regression variable dependency • Test time series autocorrelation to build a useful forecast • Use Excel add-ins to run K-means without programming • Analyze segment outliers for possible data anomalies and fraud • Build, train, and validate multiple regression models and time series forecasts Who this book is for This book is for data and business analysts as well as data science professionals. MIS, finance, and auditing professionals working with MS Excel will also find this book beneficial.

Interpretable Machine Learning

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Author :
Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Microsoft Excel 2019 Programming by Example with VBA, XML, and ASP

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Author :
Publisher : Mercury Learning and Information
ISBN 13 : 1683924010
Total Pages : 1335 pages
Book Rating : 4.6/5 (839 download)

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Book Synopsis Microsoft Excel 2019 Programming by Example with VBA, XML, and ASP by : Julitta Korol

Download or read book Microsoft Excel 2019 Programming by Example with VBA, XML, and ASP written by Julitta Korol and published by Mercury Learning and Information. This book was released on 2019-05-13 with total page 1335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated for Excel 2019 and based on the bestselling editions from previous versions, Microsoft Excel 2019 Programming by Example with VBA, XML and ASP is a practical, how-to book on Excel programming, suitable for readers already proficient with the Excel user interface (UI). If you are looking to automate Excel routine tasks, this book will progressively introduce you to programming concepts via numerous illustrated hands-on exercises. More advanced topics are demonstrated via custom projects. From recording and editing a macro and writing VBA code to working with XML documents and using Classic ASP pages to access and display data on the Web, this book takes you on a programming journey that will change the way you work with Excel. The book provides information on performing automatic operations on files, folders, and other Microsoft Office applications. It also covers proper use of event procedures, testing and debugging, and guides you through programming advanced Excel features such as PivotTables, PivotCharts, and the Ribbon interface. Features: Contains 28 chapters loaded with illustrated "Hands-On" exercises and projects that guide you through the VBA programming language. Each example tells you exactly where to enter code, how to test it, and then run it. Takes you from introductory topics--including recording and editing macros, using variables, and constants, writing subroutines/functions, conditional statements, and various methods of coding loops to repeat actions--to intermediate and advanced topics that include working with collections, class modules, arrays, file and database access, custom forms, error handling and debugging. Includes comprehensive coverage of native file handling in VBA, Windows Scripting Host (WSH), and low-level File Access. Demonstrates how to interact with Microsoft Access databases using both ADO and DAO Object Libraries to access and manipulate data. Includes chapters on programming charts, PivotTables, dialog boxes, custom forms, the Ribbon, Backstage View, context/shortcut menu customizations, as well as proper use of event procedures and callbacks. Provides a quick, “Hands-On” introduction to the data analysis and transformation processes using the Power Query feature and the “M” language formulas. Provides a practical coverage of using Web queries, HTML, XML, and VBScript in Classic ASP to retrieve and publish Excel data to the Web. ON THE COMPANION FILES (also available for download from the publisher by emailing proof of purchase to [email protected]) All source code and supplemental files for the “Hands-On” exercises and custom projects All images from the text (including 4-color screenshots)

VBA Automation for Excel 2019 Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1789616336
Total Pages : 362 pages
Book Rating : 4.7/5 (896 download)

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Book Synopsis VBA Automation for Excel 2019 Cookbook by : Mike Van Niekerk

Download or read book VBA Automation for Excel 2019 Cookbook written by Mike Van Niekerk and published by Packt Publishing Ltd. This book was released on 2020-09-18 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to gaining a 360-degree overview of the VBA programming language and learning how to build your own programs for automating routine tasks Key FeaturesExtend the capabilities of Excel and other Office applications with the help of Microsoft VBATake your Excel programming skills to the next level by creating custom applications with dialogue boxes and the range objectAutomate repetitive and monotonous office work with VBA Excel programmingBook Description Visual Basic for Applications (VBA) is a programming language developed by Microsoft to automate tasks in MS Office applications. This book will help you to focus on the essential aspects of your role by automating mundane tasks in Excel and other Office applications. With comprehensive coverage of VBA delivered in the form of practice problems and bite-sized recipes, this book will help you to hit the ground running. Unlike most books that assume prior programming experience, this book starts with the fundamentals and gradually progresses to solving bigger problems. You'll start by becoming familiar with VBA so that you can start recording macros right away. With this foundation in place, you'll advance to using the full capabilities of the language as you apply loops, functions, and custom dialog boxes to design your own automation programs. You'll also get to grips with embedded macros and other advanced tools to enhance productivity and explore topics relating to app performance and security. Throughout this VBA book, you'll cover multiple practice projects in Excel, Word, and PowerPoint while exploring tips and best practices to hone your skills. By the end of this book, you'll have developed the skills you need to use VBA to create your own programs that control MS Office applications. What you will learnUnderstand the VBA programming language's role in the context of the MS Office suiteDiscover various aspects of VBA programming such as its terminology, syntax, procedures, functions, and formsInvestigate the elements, features, and characteristics of the VBA Editor to write and edit custom scriptsAutomate Excel sheets with the help of rangesExplore error handling and debugging techniques to catch bugs in your programsCreate and use custom dialog boxes to collect data from usersCustomize and extend Office apps such as Excel, PowerPoint, and WordWho this book is for This book is for experienced Excel users, business analysts, finance professionals, and business users looking to boost their productivity by learning VBA programming to automate repetitive, tedious, or complex tasks. No prior programming experience is required to get started with this book.

Hands-On SQL Server 2019 Analysis Services

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 180020163X
Total Pages : 475 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Hands-On SQL Server 2019 Analysis Services by : Steven Hughes

Download or read book Hands-On SQL Server 2019 Analysis Services written by Steven Hughes and published by Packt Publishing Ltd. This book was released on 2020-10-22 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up to speed with the new features added to Microsoft SQL Server 2019 Analysis Services and create models to support your business Key FeaturesExplore tips and tricks to design, develop, and optimize end-to-end data analytics solutions using Microsoft's technologiesLearn tabular modeling and multi-dimensional cube design development using real-world examplesImplement Analysis Services to help you make productive business decisionsBook Description SQL Server Analysis Services (SSAS) continues to be a leading enterprise-scale toolset, enabling customers to deliver data and analytics across large datasets with great performance. This book will help you understand MS SQL Server 2019’s new features and improvements, especially when it comes to SSAS. First, you’ll cover a quick overview of SQL Server 2019, learn how to choose the right analytical model to use, and understand their key differences. You’ll then explore how to create a multi-dimensional model with SSAS and expand on that model with MDX. Next, you’ll create and deploy a tabular model using Microsoft Visual Studio and Management Studio. You'll learn when and how to use both tabular and multi-dimensional model types, how to deploy and configure your servers to support them, and design principles that are relevant to each model. The book comes packed with tips and tricks to build measures, optimize your design, and interact with models using Excel and Power BI. All this will help you visualize data to gain useful insights and make better decisions. Finally, you’ll discover practices and tools for securing and maintaining your models once they are deployed. By the end of this MS SQL Server book, you’ll be able to choose the right model and build and deploy it to support the analytical needs of your business. What you will learnDetermine the best analytical model using SSASCover the core aspects involved in MDX, including writing your first queryImplement calculated tables and calculation groups (new in version 2019) in DAXCreate and deploy tabular and multi-dimensional models on SQL 2019Connect and create data visualizations using Excel and Power BIImplement row-level and other data security methods with tabular and multi-dimensional modelsExplore essential concepts and techniques to scale, manage, and optimize your SSAS solutionsWho this book is for This Microsoft SQL Server book is for BI professionals and data analysts who are looking for a practical guide to creating and maintaining tabular and multi-dimensional models using SQL Server 2019 Analysis Services. A basic working knowledge of BI solutions such as Power BI and database querying is required.

Handbook of Research on Acquiring 21st Century Literacy Skills Through Game-Based Learning

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Author :
Publisher : IGI Global
ISBN 13 : 1799872734
Total Pages : 958 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Acquiring 21st Century Literacy Skills Through Game-Based Learning by : Lane, Carol-Ann

Download or read book Handbook of Research on Acquiring 21st Century Literacy Skills Through Game-Based Learning written by Lane, Carol-Ann and published by IGI Global. This book was released on 2022-01-07 with total page 958 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging technologies are becoming more prevalent in global classrooms. Traditional literacy pedagogies are shifting toward game-based pedagogy, addressing 21st century learners. Therefore, within this context there remains a need to study strategies to engage learners in meaning-making with some element of virtual design. Technology supports the universal design learning framework because it can increase the access to meaningful engagement in learning and reduce barriers. The Handbook of Research on Acquiring 21st Century Literacy Skills Through Game-Based Learning provides theoretical frameworks and empirical research findings in digital technology and multimodal ways of acquiring literacy skills in the 21st century. This book gains a better understanding of how technology can support leaner frameworks and highlights research on discovering new pedagogical boundaries by focusing on ways that the youth learn from digital sources such as video games. Covering topics such as elementary literacy learning, indigenous games, and student-worker training, this book is an essential resource for educators in K-12 and higher education, school administrators, academicians, pre-service teachers, game developers, researchers, and libraries.

Hands-On Exploratory Data Analysis with Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 178953562X
Total Pages : 342 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Hands-On Exploratory Data Analysis with Python by : Suresh Kumar Mukhiya

Download or read book Hands-On Exploratory Data Analysis with Python written by Suresh Kumar Mukhiya and published by Packt Publishing Ltd. This book was released on 2020-03-27 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.

A Hands-On Introduction to Data Science

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1108472443
Total Pages : 459 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis A Hands-On Introduction to Data Science by : Chirag Shah

Download or read book A Hands-On Introduction to Data Science written by Chirag Shah and published by Cambridge University Press. This book was released on 2020-04-02 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.

Data Smart

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1118839862
Total Pages : 432 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Data Smart by : John W. Foreman

Download or read book Data Smart written by John W. Foreman and published by John Wiley & Sons. This book was released on 2013-10-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365)

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Author :
Publisher : Microsoft Press
ISBN 13 : 0137613679
Total Pages : 1788 pages
Book Rating : 4.1/5 (376 download)

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Book Synopsis Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) by : Wayne Winston

Download or read book Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) written by Wayne Winston and published by Microsoft Press. This book was released on 2021-12-17 with total page 1788 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master business modeling and analysis techniques with Microsoft Excel and transform data into bottom-line results. Award-winning educator Wayne Winston's hands-on, scenario-focused guide helps you use today's Excel to ask the right questions and get accurate, actionable answers. More extensively updated than any previous edition, new coverage ranges from one-click data analysis to STOCKHISTORY, dynamic arrays to Power Query, and includes six new chapters. Practice with over 900 problems, many based on real challenges faced by working analysts. Solve real problems with Microsoft Excel—and build your competitive advantage Quickly transition from Excel basics to sophisticated analytics Use recent Power Query enhancements to connect, combine, and transform data sources more effectively Use the LAMBDA and LAMBDA helper functions to create Custom Functions without VBA Use New Data Types to import data including stock prices, weather, information on geographic areas, universities, movies, and music Build more sophisticated and compelling charts Use the new XLOOKUP function to revolutionize your lookup formulas Master new Dynamic Array formulas that allow you to sort and filter data with formulas and find all UNIQUE entries Illuminate insights from geographic and temporal data with 3D Maps Improve decision-making with probability, Bayes' theorem, and Monte Carlo simulation and scenarios Use Excel trend curves, multiple regression, and exponential smoothing for predictive analytics Use Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook

Feature Engineering for Machine Learning

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491953195
Total Pages : 218 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Feature Engineering for Machine Learning by : Alice Zheng

Download or read book Feature Engineering for Machine Learning written by Alice Zheng and published by "O'Reilly Media, Inc.". This book was released on 2018-03-23 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques