[PDF] Full Mineria De Datos E Ia Conceptos Fundamentos Y Aplicaciones Download eBook

Minería de Datos e IA : Conceptos, Fundamentos y Aplicaciones

Author: Enrico Guardelli

Publisher: MedTechBiz

Published: 2024-07-18

Total Pages: 190

ISBN-13:

Este libro ofrece una introducción completa y accesible a los campos de la minería de datos y la inteligencia artificial. Cubre todo, desde conceptos básicos hasta estudios de casos avanzados, con énfasis en la aplicación práctica utilizando herramientas como Python y R. También aborda cuestiones críticas de ética y responsabilidad en el uso de estas tecnologías, discutiendo temas como la privacidad, el sesgo algorítmico y transparencia. El objetivo es permitir al lector aplicar técnicas de minería de datos e inteligencia artificial a problemas reales, contribuyendo a la innovación y el progreso en su área de especialización.

Minería De Datos E Inteligencia Artificial (ia)

Author: Enrinco Guardelli

Publisher: Clube de Autores

Published: 2024-06-06

Total Pages: 243

ISBN-13:

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Este libro ofrece una introducción completa y accesible a los campos de la minería de datos y la inteligencia artificial. Cubre todo, desde conceptos básicos hasta estudios de casos avanzados, con énfasis en la aplicación práctica utilizando herramientas como Python y R. También aborda cuestiones críticas de ética y responsabilidad en el uso de estas tecnologías, discutiendo temas como la privacidad, el sesgo algorítmico y transparencia. El objetivo es permitir al lector aplicar técnicas de minería de datos e inteligencia artificial a problemas reales, contribuyendo a la innovación y el progreso en su área de especialización.

Minería De Datos E Ia

Author: Enrico Guardelli

Publisher: Clube de Autores

Published: 2024-06-26

Total Pages: 190

ISBN-13:

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La minería de datos y la inteligencia artificial (IA) emergen como disciplinas centrales para transformar los datos en conocimientos valiosos. La integración de la minería de datos y la IA permite la automatización de procesos complejos, la previsión de tendencias y la toma de decisiones autónoma. Este libro ofrece una introducción completa y accesible a estos campos, desde conceptos básicos hasta estudios de casos avanzados, con énfasis en la aplicación práctica utilizando herramientas como Python y R. El objetivo es permitir al lector aplicar técnicas de minería de datos e inteligencia artificial a problemas reales, contribuyendo a la innovación y el progreso en su campo.

Applications of Big Data Analytics

Author: Mohammed M. Alani

Publisher: Springer

Published: 2019-02-09

Total Pages: 0

ISBN-13: 9783030094973

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This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

Data Mining and Learning Analytics

Author: Samira ElAtia

Publisher: John Wiley & Sons

Published: 2016-09-20

Total Pages: 351

ISBN-13: 1118998219

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Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.

RETRACTED BOOK: 151 Trading Strategies

Author: Zura Kakushadze

Publisher: Springer

Published: 2018-12-13

Total Pages: 480

ISBN-13: 3030027929

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The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.

NANDA International Nursing Diagnoses

Author: Heather T. Herdman

Publisher: Thieme

Published: 2017-06-28

Total Pages: 526

ISBN-13: 1626239304

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Fully updated and revised by authors T. Heather Herdman, PhD, RN, FNI, and Shigemi Kamitsuru, PhD, RN, FNI, Nursing Diagnoses: Definitions and Classification 2018-2020, Eleventh Edition is the definitive guide to nursing diagnoses, as reviewed and approved by NANDA International (NANDA-I). In this new edition of a seminal text, the authors have written all introductory chapters at an undergraduate nursing level, providing the critical information needed for nurses to understand assessment, its link to diagnosis and clinical reasoning, and the purpose and use of taxonomic structure for the nurse at the bedside. Other changes include: 18 new nursing diagnoses and 72 revised diagnoses Updates to 11 nursing diagnosis labels, ensuring they are consistent with current literature and reflect a human response Modifications to the vast majority of the nursing diagnosis definitions, including especially Risk Diagnoses Standardization of diagnostic indicator terms (defining characteristics, related factors, risk factors, associated conditions, and at-risk populations) to further aid clarity for readers and clinicians Coding of all diagnostic indicator terms for those using electronic versions of the terminology Web-based resources include chapter and reference lists for new diagnoses Rigorously updated and revised, Nursing Diagnoses: Definitions and Classification 2018-2020, Eleventh Edition is a must-have resource for all nursing students, professional nurses, nurse educators, nurse informaticists, and nurse administrators.

bookdown

Author: Yihui Xie

Publisher: CRC Press

Published: 2016-12-12

Total Pages: 140

ISBN-13: 1351792601

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bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub.