Angebote zu "Model-Based" (424 Treffer)

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Sesame Price Prediction Using Artificial Neural...
29,99 € *
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Master's Thesis from the year 2019 in the subject Computer Science - Miscellaneous, University of Gondar (Atse Tewodros Cumpas), course: Information technology, language: English, abstract: Agricultural price predictions are an integral component of trade and policy analysis. As the prices of agricultural commodities directly influence the real income of farmers and it also affects the national foreign currency generate. Sesame is highly produced in some tropical and subtropical rain forest Ethiopia region. The thesis is to build a model that can predict market prices of sesame commodity. Based on the complexity of sesame price prediction; the predicting models used for crop are linear regression, support vector machine and neural network models to predict a future price. A data have been taken from the ECX website (www.ecx.com.et) in the interval of January 2013 to March 2019. The total numbers of records selected to the experiments are 5,327 daily prices are used for proposed models. The experimental result had evaluated by RMSE, MSE and CC metrics. We follow six phase CRISP-DM process model for sesame price prediction. The process phase are, business understanding, data understanding, data preparation, modeling, evaluating and deployment.

Anbieter: buecher
Stand: 07.04.2020
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Yeast
61,99 € *
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Finally, a stand-alone, all-inclusive textbook on yeast biology. Based on the feedback resulting from his highly successful monograph, Horst Feldmann has totally rewritten he contents to produce a comprehensive, student-friendly textbook on the topic. The scope has been widened, with almost double the content so as to include all aspects of yeast biology, from genetics via cell biology right up to biotechnology applications. The cell and molecular biology sections have been vastly expanded, while information on other yeast species has been added, with contributions from additional authors. Naturally, the illustrations are in full color throughout, and the book is backed by a complimentary website. The resulting textbook caters to the needs of an increasing number of students in biomedical research, cell and molecular biology, microbiology and biotechnology who end up using yeast as an important tool or model organism.

Anbieter: buecher
Stand: 07.04.2020
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Yeast
61,99 € *
ggf. zzgl. Versand

Finally, a stand-alone, all-inclusive textbook on yeast biology. Based on the feedback resulting from his highly successful monograph, Horst Feldmann has totally rewritten he contents to produce a comprehensive, student-friendly textbook on the topic. The scope has been widened, with almost double the content so as to include all aspects of yeast biology, from genetics via cell biology right up to biotechnology applications. The cell and molecular biology sections have been vastly expanded, while information on other yeast species has been added, with contributions from additional authors. Naturally, the illustrations are in full color throughout, and the book is backed by a complimentary website. The resulting textbook caters to the needs of an increasing number of students in biomedical research, cell and molecular biology, microbiology and biotechnology who end up using yeast as an important tool or model organism.

Anbieter: buecher
Stand: 07.04.2020
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Programming: Python Programming and Machine Lea...
9,95 € *
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Python ProgrammingQuick Python tour: Build a simple demo that includes data representation, object-oriented programming, object persistence, GUIs, and website basicsSystem programming: Explore system interface tools and techniques for command-line scripting, processing files and folders, running programs in parallel, and moreGUI programming: Learn to use Python’s tkinter widget libraryInternet programming: Access client-side network protocols and email tools, use CGI scripts, and learn website implementation techniquesMore ways to apply Python: Implement data structures, parse text-based information, interface with databases, and extend and embed PythonMachine LearningHow to download free datasetsWhat tools and machine learning libraries you needData scrubbing techniques, including one-hot encoding, binning and dealing with missing dataPreparing data for analysis, including k-fold ValidationRegression analysis to create trend linesClustering, including k-means and k-nearest NeighborsThe basics of Neural NetworksBias/Variance to improve your machine learning modelDecision Trees to decode classificationHow to build your first Machine Learning Model to predict house values using Python 1. Language: English. Narrator: Chris Clyne, Steven Barnett. Audio sample: http://samples.audible.de/bk/acx0/183219/bk_acx0_183219_sample.mp3. Digital audiobook in aax.

Anbieter: Audible
Stand: 07.04.2020
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Introduction to Time Series and Forecasting
76,99 € *
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This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series Introductions to Brownian motion, Lévy processes and Itô calculus An expanded section on continuous-time ARMA processes

Anbieter: buecher
Stand: 07.04.2020
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Introduction to Time Series and Forecasting
74,89 € *
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This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series Introductions to Brownian motion, Lévy processes and Itô calculus An expanded section on continuous-time ARMA processes

Anbieter: buecher
Stand: 07.04.2020
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The Complete Google AdWords and YouTube Adverti...
9,95 € *
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Would you try listening to this book today to make your experience with Google AdWords and YouTube advertising easier than mine was? In 2011 when I started using Google AdWords to get clicks to my website and promote my business online, I wasted thousands of dollars getting clicks I did not need and hundreds of hours working with the ads only to get my account suspended as soon as I got a positive ROI. By 2012, I started managing Google AdWords for clients based on my experience failing to do my own ads successfully. Amazingly, client ads were often easier to do than my own and inspired me to try a new approach to AdWords using YouTube advertising, also known as Google AdWords for video. YouTube now is my biggest asset online thanks to YouTube advertising and continues to help me build deeper relationships with followers and customers that just watched one video. Four years after I got my first AdWords account suspended, I gained enough courage to try again on advertising my online courses with a new website and new business model. From the beginning, I was getting sales for $20 in ad spend and eventually got down to sales consistently for $5 with display ads and $8 with search ads. When this was combined with the higher ranking on Udemy and the organic search traffic follow up from students sharing the courses, my work on Google AdWords became part of a multimillion dollar sales system selling courses online. That sounded impressive right? Good, because I love to try and impress everyone with how smart I am and the story takes a dramatic downturn from there! Listen to the book today to hear the rest! 1. Language: English. Narrator: Jerry Banfield. Audio sample: http://samples.audible.de/bk/acx0/074901/bk_acx0_074901_sample.mp3. Digital audiobook in aax.

Anbieter: Audible
Stand: 07.04.2020
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Latent Variable Modeling Using R (eBook, PDF)
44,95 € *
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This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book's examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter's exercises. Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.

Anbieter: buecher
Stand: 07.04.2020
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Latent Variable Modeling Using R (eBook, PDF)
44,95 € *
ggf. zzgl. Versand

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book's examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter's exercises. Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.

Anbieter: buecher
Stand: 07.04.2020
Zum Angebot