R for Data Science

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

The Publishers' Trade List Annual

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Publisher :
ISBN 13 :
Total Pages : 1510 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis The Publishers' Trade List Annual by :

Download or read book The Publishers' Trade List Annual written by and published by . This book was released on 1980 with total page 1510 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Programación en R para ciencia de datos

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Author :
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (781 download)

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Book Synopsis Programación en R para ciencia de datos by : Caroline Davis

Download or read book Programación en R para ciencia de datos written by Caroline Davis and published by Independently Published. This book was released on 2023-02-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Programación en R para ciencia de datos" es un libro dirigido a cualquier persona que desee aprender el lenguaje de programación R para la ciencia de datos. Con un enfoque práctico y paso a paso, el libro introduce a los lectores en los conceptos fundamentales de la programación en R, proporcionando una sólida base para el análisis y la visualización de datos. El libro cubre una amplia gama de temas, desde la importación de datos hasta la manipulación de datos, desde la modelización estadística hasta la creación de gráficos atractivos. En cada capítulo, el libro ofrece ejemplos concretos de código y explicaciones detalladas, acompañadas de imágenes claras y concisas. Con "Programación en R para ciencia de datos", los lectores aprenderán a: Importar y manipular datos en diferentes formatos Realizar análisis estadísticos y construir modelos predictivos Visualizar datos de manera clara y atractiva Escribir funciones personalizadas y crear paquetes R Utilizar R para la ciencia de datos en contextos reales, como la economía, la biología y las finanzas. El libro es adecuado tanto para principiantes como para usuarios experimentados de R que deseen mejorar sus habilidades de análisis de datos. Con su cobertura completa, explicaciones claras y tono accesible, "Programación en R para ciencia de datos" es una excelente fuente para cualquiera que desee dominar uno de los lenguajes de programación más potentes para la ciencia de datos.

R for Business Analytics

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Publisher : Springer Science & Business Media
ISBN 13 : 1461443423
Total Pages : 322 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis R for Business Analytics by : A Ohri

Download or read book R for Business Analytics written by A Ohri and published by Springer Science & Business Media. This book was released on 2012-09-14 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines common tasks performed by business analysts and helps the reader navigate the wealth of information in R and its 4000 packages to create useful analytics applications. Includes interviews with corporate users of R, and easy-to-use examples.

Estadística práctica para ciencia de datos con R y Python

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Publisher : Marcombo
ISBN 13 : 8426734545
Total Pages : 439 pages
Book Rating : 4.4/5 (267 download)

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Book Synopsis Estadística práctica para ciencia de datos con R y Python by : Peter Bruce

Download or read book Estadística práctica para ciencia de datos con R y Python written by Peter Bruce and published by Marcombo. This book was released on 2022-02-10 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Los métodos estadísticos son una parte fundamental de la ciencia de datos, pero pocos científicos de datos tienen una formación avanzada en estadística. Los cursos y libros sobre estadística básica rara vez tratan el tema desde la perspectiva de la ciencia de datos. La segunda edición de este libro incluye ejemplos detallados de Python, ofrece una orientación práctica sobre la aplicación de los métodos estadísticos a la ciencia de datos, te indica cómo evitar su uso incorrecto y te aconseja sobre lo que es y lo que no es importante. Muchos recursos de la ciencia de datos incorporan métodos estadísticos, pero carecen de una perspectiva estadística más profunda. Si estás familiarizado con los lenguajes de programación R o Python y tienes algún conocimiento de estadística, este libro suple esas carencias de una forma práctica, accesible y clara. Con este libro aprenderás: Por qué el análisis exploratorio de datos es un paso preliminar clave en la ciencia de datos Cómo el muestreo aleatorio puede reducir el sesgo y ofrecer un conjunto de datos de mayor calidad, incluso con Big Data Cómo los principios del diseño experimental ofrecen respuestas definitivas a preguntas Cómo utilizar la regresión para estimar resultados y detectar anomalías Técnicas de clasificación esenciales para predecir a qué categorías pertenece un registro Métodos estadísticos de aprendizaje automático que "aprenden" a partir de los datos Métodos de aprendizaje no supervisados para extraer significado de datos sin etiquetar Peter Bruce es el fundador del Institute for Statistics Education en Statistics.com. Andrew Bruce es científico investigador jefe en Amazon y tiene más de 30 años de experiencia en estadística y ciencia de datos. Peter Gedeck es científico de datos senior en Collaborative Drug Discovery, desarrolla algoritmos de aprendizaje automático para pronosticar propiedades de posibles futuros fármacos.

Python Data Science Handbook

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912138
Total Pages : 609 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Python Data Science Handbook by : Jake VanderPlas

Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Decision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances

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Author :
Publisher : IGI Global
ISBN 13 : 1615208828
Total Pages : 554 pages
Book Rating : 4.6/5 (152 download)

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Book Synopsis Decision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances by : Manos, Basil

Download or read book Decision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances written by Manos, Basil and published by IGI Global. This book was released on 2010-06-30 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: As national and international concern over sustainable resources becomes more prevalent, the need for decision support systems (DSS) increases. The applicable uses of a successful system can assist in the sustainability of resources, as well as the efficiency and management of the agri-environment industry. Decision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances presents the development of DSS for managing agricultural and environmental systems, focusing on the exposition of innovative methodologies, from web-mobile systems to artificial intelligence and knowledge-based DSS, as well as their applications in every aspect from harvest planning to international food production and land management. This book provides an in depth look into the growing importance of DSS in agriculture.

Artificial Intelligence, Computer and Software Engineering Advances

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Publisher : Springer Nature
ISBN 13 : 3030680800
Total Pages : 489 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Artificial Intelligence, Computer and Software Engineering Advances by : Miguel Botto-Tobar

Download or read book Artificial Intelligence, Computer and Software Engineering Advances written by Miguel Botto-Tobar and published by Springer Nature. This book was released on 2021-04-20 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the XV Multidisciplinary International Congress on Science and Technology (CIT 2020), held in Quito, Ecuador, on 26–30 October 2020, proudly organized by Universidad de las Fuerzas Armadas ESPE in collaboration with GDEON. CIT is an international event with a multidisciplinary approach that promotes the dissemination of advances in Science and Technology research through the presentation of keynote conferences. In CIT, theoretical, technical, or application works that are research products are presented to discuss and debate ideas, experiences, and challenges. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Artificial Intelligence Computational Modeling Data Communications Defense Engineering Innovation, Technology, and Society Managing Technology & Sustained Innovation, and Business Development Modern Vehicle Technology Security and Cryptography Software Engineering

R for Data Science

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Publisher :
ISBN 13 : 9781491910382
Total Pages : pages
Book Rating : 4.9/5 (13 download)

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Book Synopsis R for Data Science by : Hadley Wickham. Garrett Grolemund

Download or read book R for Data Science written by Hadley Wickham. Garrett Grolemund and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

A User’s Guide to Network Analysis in R

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Publisher : Springer
ISBN 13 : 3319238833
Total Pages : 241 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis A User’s Guide to Network Analysis in R by : Douglas Luke

Download or read book A User’s Guide to Network Analysis in R written by Douglas Luke and published by Springer. This book was released on 2015-12-14 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

Ciencia

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Publisher :
ISBN 13 :
Total Pages : 476 pages
Book Rating : 4.A/5 ( download)

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Book Synopsis Ciencia by :

Download or read book Ciencia written by and published by . This book was released on 2007 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Data Science

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Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 836 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Introduction to Data Science by : Rafael A. Irizarry

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Introduction to Statistics and Data Analysis

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Publisher : Springer Nature
ISBN 13 : 3031118332
Total Pages : 584 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Introduction to Statistics and Data Analysis by : Christian Heumann

Download or read book Introduction to Statistics and Data Analysis written by Christian Heumann and published by Springer Nature. This book was released on 2023-01-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.

Mathematics for Machine Learning

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Publisher : Cambridge University Press
ISBN 13 : 1108569323
Total Pages : 392 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth

Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Human-Computer Interaction

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Publisher : Springer Nature
ISBN 13 : 303037386X
Total Pages : 451 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Human-Computer Interaction by : Pablo H. Ruiz

Download or read book Human-Computer Interaction written by Pablo H. Ruiz and published by Springer Nature. This book was released on 2019-12-14 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 5th Iberoamerican Workshop on Human-Computer Interaction, HCI-Collab 2019, held in Puebla, Mexico, in June 2019. The 31 full papers presented in this volume were carefully reviewed and selected from 55 submissions. The papers describe models, design patterns, implementations, evaluations of existing applications, and systemic reviews; all of which are very important aspects within HCI.

R Programming for Data Science

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Publisher :
ISBN 13 : 9781365056826
Total Pages : 0 pages
Book Rating : 4.0/5 (568 download)

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Book Synopsis R Programming for Data Science by : Roger D. Peng

Download or read book R Programming for Data Science written by Roger D. Peng and published by . This book was released on 2012-04-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.

Sams Teach Yourself Active Server Pages 3.0 in 21 Days

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Publisher : Pearson Educación
ISBN 13 : 9789684445277
Total Pages : 812 pages
Book Rating : 4.4/5 (452 download)

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Book Synopsis Sams Teach Yourself Active Server Pages 3.0 in 21 Days by : Scott Mitchell

Download or read book Sams Teach Yourself Active Server Pages 3.0 in 21 Days written by Scott Mitchell and published by Pearson Educación. This book was released on 2000 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to ASP and IIS fundamentals covers dynamic content, interactivity, writing files on the Web server, personalizing content, reading databases, and debugging scripts.