Data Forecasting and Segmentation Using Microsoft Excel

Name: Data Forecasting and Segmentation Using Microsoft Excel
Brand: Packt Publishing
SKU: 1560672

Cargando comentarios…

$779

$701

Envío gratis siempre

Comentarios

Cargando el resumen…

Por favor, inicia sesión para escribir un comentario.

Cargando comentarios…

1581594Data Forecasting and Segmentation Using Microsoft Excelhttps://www.gandhi.com.mx/data-forecasting-and-segmentation-using-microsoft-excel/phttps://gandhi.vtexassets.com/arquivos/ids/850004/8e00ecd8-11a8-48c5-ae63-4ae128d6803b.jpg?v=638336473145900000701779MXNPackt PublishingInStock/Ebooks/<p>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. Youll 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, youll 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, youll be able to use the classification algorithm to group data with different variables. Youll 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.</p>...1560672Data Forecasting and Segmentation Using Microsoft Excel701779https://www.gandhi.com.mx/data-forecasting-and-segmentation-using-microsoft-excel/phttps://gandhi.vtexassets.com/arquivos/ids/850004/8e00ecd8-11a8-48c5-ae63-4ae128d6803b.jpg?v=638336473145900000InStockMXN99999DIEbook20229781803235264_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_pstrongPerform time series forecasts, linear prediction, and data segmentation with no-code Excel machine learning/strong/ph4Key Features/h4ulliSegment data, regression predictions, and time series forecasts without writing any code/liliGroup multiple variables with K-means using Excel plugin without programming/liliBuild, validate, and predict with a multiple linear regression model and time series forecasts/li/ulh4Book Description/h4pData 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./ppYoull 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, youll be able to detect outliers that could indicate possible fraud or a bad function in network packets./ppBy the end of this Microsoft Excel book, youll be able to use the classification algorithm to group data with different variables. Youll also be able to train linear and time series models to perform predictions and forecasts based on past data./ph4What you will learn/h4ulliUnderstand why machine learning is important for classifying data segmentation/liliFocus on basic statistics tests for regression variable dependency/liliTest time series autocorrelation to build a useful forecast/liliUse Excel add-ins to run K-means without programming/liliAnalyze segment outliers for possible data anomalies and fraud/liliBuild, train, and validate multiple regression models and time series forecasts/li/ulh4Who this book is for/h4pThis 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./p(*_*)9781803235264_<p>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. Youll 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, youll 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, youll be able to use the classification algorithm to group data with different variables. Youll 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.</p>...9781803235264_Packt Publishinglibro_electonico_1bb15733-a0a1-3562-99f8-3e8fdbd1aebc_9781803235264;9781803235264_9781803235264Fernando RoqueInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/packt-epub-598ce84a-bd26-4181-bf18-e7336603ed78.epub2022-05-27T00:00:00+00:00Packt Publishing