Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Analitica Predictiva
Download Analitica Predictiva full books in PDF, epub, and Kindle. Read online Analitica Predictiva ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Customer analytics by : Núria Braulio Gil
Download or read book Customer analytics written by Núria Braulio Gil and published by Editorial UOC. This book was released on 2015-01-01 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Las organizaciones han usado estrategias, como la inteligencia de negocio, para tomar mejores decisiones a partir de los datos. Actualmente, en la era de los datos, nuestros clientes son más inteligentes, están más informados y ya no son tan leales con nuestra marca. Esperan experiencias inolvidables y profundamente personalizadas en cada una de las interacciones con nuestra organización. Como resultado, las organizaciones están obligadas a transformar sus estrategias para conocer mejor las necesidades y preferencias de sus clientes, basándose en una enorme cantidad de datos.
Book Synopsis Metadata and Semantics Research by : Emmanouel Garoufallou
Download or read book Metadata and Semantics Research written by Emmanouel Garoufallou and published by Springer. This book was released on 2015-09-03 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th Metadata and Semantics Research Conference, MTSR 2015, held in Manchester, UK, in September 2015.The 35 full papers and 3 short papers presented together with 2 poster papers were carefully reviewed and selected from 76 submissions. The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.
Book Synopsis Flexible Query Answering Systems by : Henning Christiansen
Download or read book Flexible Query Answering Systems written by Henning Christiansen and published by Springer. This book was released on 2017-06-16 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Flexible Query Answering Systems, FQAS 2017, held in London, UK, in June 2017. The 21 full papers presented in this book together with 4 short papers were carefully reviewed and selected from 43 submissions. The papers cover the following topics: foundations of flexible querying; recommendation and ranking; technologies for flexible representations and querying; knowledge discovery and information/data retrieval; intuitionistic sets; and generalized net model.
Book Synopsis Estrategias tecnológicas para la industria de la hostelería by : Peter D. Nyheim
Download or read book Estrategias tecnológicas para la industria de la hostelería written by Peter D. Nyheim and published by Ediciones Universidad Católica de Salta. This book was released on 2019-10-22 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Los procesos comerciales en la industria de la hostelería, como toda industria en la actualidad, están atravesados por las nuevas tecnologías que aportan rapidez, eficiencia y posibilidad de control al ámbito de la gestión. La industria del turismo, y en especial todo lo relacionado con el hospedaje y la alimentación del viajero, se mueve con una fuerte dinámica, y la rapidez de la respuesta es uno de los aspectos prioritarios junto con la necesidad de lograr la total satisfacción de las demandas tanto de clientes como de proveedores. En todos estos procesos, las tecnologías de la información (TI), los sistemas de información (IS) y los sistemas de gestión de la información (MIS) son la herramienta clave en el éxito de los procesos vinculados tanto en las operaciones diarias como en la planificación. Este libro, dirigido tanto a estudiantes como a profesionales vinculados a la hostelería, es el resultado de una colaboración entre autores que han vivido las situaciones que se plantean en él. Cada capítulo cuenta con entrevistas a líderes de la industria en las que se reconocen casos concretos de aplicación de tecnología en la hostelería. Sin dudas, las nuevas tecnologías ofrecen un mayor número de oportunidades tanto a gerentes como a clientes; desde hacer una reserva a través de una aplicación, hasta la experimentación de un servicio mediante recursos tecnológicos de realidad aumentada. De ahí la importancia, necesidad y pertinencia de este libro, que alcanza con esta su tercera edición, primera en español.
Download or read book Qüestiió written by and published by . This book was released on 1997 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Index Veterinarius written by and published by . This book was released on 1998 with total page 1762 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predictive HR Analytics by : Dr Martin R. Edwards
Download or read book Predictive HR Analytics written by Dr Martin R. Edwards and published by Kogan Page Publishers. This book was released on 2019-03-03 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: HR metrics and organizational people-related data are an invaluable source of information from which to identify trends and patterns in order to make effective business decisions. But HR practitioners often lack the statistical and analytical know-how to fully harness the potential of this data. Predictive HR Analytics provides a clear, accessible framework for understanding and working with people analytics and advanced statistical techniques. Using the statistical package SPSS (with R syntax included), it takes readers step by step through worked examples, showing them how to carry out and interpret analyses of HR data in areas such as employee engagement, performance and turnover. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies. This second edition has been updated to include the latest material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using survival analyses, and up-to-the-minute screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.
Download or read book Trabajos de estadística written by and published by . This book was released on 1991 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predictive Analytics for the Modern Enterprise by : Nooruddin Abbas Ali
Download or read book Predictive Analytics for the Modern Enterprise written by Nooruddin Abbas Ali and published by "O'Reilly Media, Inc.". This book was released on 2024-05-20 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow
Book Synopsis Predictive Analytics by : Vijay Kumar
Download or read book Predictive Analytics written by Vijay Kumar and published by CRC Press. This book was released on 2021-01-14 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.
Book Synopsis Judgment in Predictive Analytics by : Matthias Seifert
Download or read book Judgment in Predictive Analytics written by Matthias Seifert and published by Springer Nature. This book was released on 2023-06-02 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and showcases the state-of-the-art in judgment-based predictive analytics. In recent years, technological advancements have made it possible to use predictive analytics to exploit highly complex (big) data resources. Consequently, modern forecasting methodologies are based on sophisticated algorithms from the domain of machine learning and deep learning. However, research shows that in the majority of industry contexts, human judgment remains an indispensable component of the managerial forecasting process. This book discusses ways in which decision-makers can address human behavioral issues in judgmental forecasting. The book begins by introducing readers to the notion of human-machine interactions. This includes a look at the necessity of managerial judgment in situations where organizations commonly have algorithmic decision support models at their disposal. The remainder of the book is divided into three parts, with Part I focusing on the role of individual-level judgment in the design and utilization of algorithmic models. The respective chapters cover individual-level biases such as algorithm aversion, model selection criteria, model-judgment aggregation issues and implications for behavioral change. In turn, Part II addresses the role of collective judgments in predictive analytics. The chapters focus on issues related to talent spotting, performance-weighted aggregation, and the wisdom of timely crowds. Part III concludes the book by shedding light on the importance of contextual factors as critical determinants of forecasting performance. Its chapters discuss the usefulness of scenario analysis, the role of external factors in time series forecasting and introduce the idea of mindful organizing as an approach to creating more sustainable forecasting practices in organizations.
Book Synopsis Predictive Analytics Using Statistics and Big Data: Concepts and Modeling by : Krishna Kumar Mohbey
Download or read book Predictive Analytics Using Statistics and Big Data: Concepts and Modeling written by Krishna Kumar Mohbey and published by Bentham Science Publishers. This book was released on 2020-12-09 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of the latest and representative developments in predictive analytics using big data technologies. It focuses on some critical aspects of big data and machine learning and provides studies for readers. The chapters address a comprehensive range of advanced data technologies used for statistical modeling towards predictive analytics. Topics included in this book include: - Categorized machine learning algorithms - Player monopoly in cricket teams. - Chain type estimators - Log type estimators - Bivariate survival data using shared inverse Gaussian frailty models - Weblog analysis - COVID-19 epidemiology This reference book will be of significant benefit to the predictive analytics community as a useful guide of the latest research in this emerging field.
Book Synopsis Predictive Analytics by : Eric Siegel
Download or read book Predictive Analytics written by Eric Siegel and published by John Wiley & Sons. This book was released on 2016-01-12 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a
Book Synopsis Data Science and Predictive Analytics by : Ivo D. Dinov
Download or read book Data Science and Predictive Analytics written by Ivo D. Dinov and published by Springer Nature. This book was released on 2023-02-16 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges. Each concept in the book includes a rigorous symbolic formulation coupled with computational algorithms and complete end-to-end pipeline protocols implemented as functional R electronic markdown notebooks. These workflows support active learning and demonstrate comprehensive data manipulations, interactive visualizations, and sophisticated analytics. The content includes open problems, state-of-the-art scientific knowledge, ethical integration of heterogeneous scientific tools, and procedures for systematic validation and dissemination of reproducible research findings. Complementary to the enormous challenges related to handling, interrogating, and understanding massive amounts of complex structured and unstructured data, there are unique opportunities that come with access to a wealth of feature-rich, high-dimensional, and time-varying information. The topics covered in Data Science and Predictive Analytics address specific knowledge gaps, resolve educational barriers, and mitigate workforce information-readiness and data science deficiencies. Specifically, it provides a transdisciplinary curriculum integrating core mathematical principles, modern computational methods, advanced data science techniques, model-based machine learning, model-free artificial intelligence, and innovative biomedical applications. The book’s fourteen chapters start with an introduction and progressively build foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning. The second edition of the book includes additional learning-based strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic appendices. This textbook is suitable for formal didactic instructor-guided course education, as well as for individual or team-supported self-learning. The material is presented at the upper-division and graduate-level college courses and covers applied and interdisciplinary mathematics, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical sciences. The analytical techniques and predictive scientific methods described in the book may be useful to a wide range of readers, formal and informal learners, college instructors, researchers, and engineers throughout the academy, industry, government, regulatory, funding, and policy agencies. The supporting book website provides many examples, datasets, functional scripts, complete electronic notebooks, extensive appendices, and additional materials.
Book Synopsis Predictive Analytics with KNIME by : Frank Acito
Download or read book Predictive Analytics with KNIME written by Frank Acito and published by Springer Nature. This book was released on 2024-01-03 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decision trees, and others) are covered with conceptual background as well as demonstrations of KNIME using each tool. The book uses KNIME, which is a comprehensive, open-source software tool for analytics that does not require coding but instead uses an intuitive drag-and-drop workflow to create a network of connected nodes on an interactive canvas. KNIME workflows provide graphic representations of each step taken in analyses, making the analyses self-documenting. The graphical documentation makes it easy to reproduce analyses, as well as to communicate methods and results to others. Integration with R is also available in KNIME, and several examples using R nodes in a KNIME workflow are demonstrated for special functions and tools not explicitly included in KNIME.
Book Synopsis Predictive Analytics using R by : Jeffrey Strickland
Download or read book Predictive Analytics using R written by Jeffrey Strickland and published by Lulu.com. This book was released on 2015-01-16 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.
Book Synopsis Predictive Analytics Using Statistics and Big Data by : Krishna Kumar Mohbey
Download or read book Predictive Analytics Using Statistics and Big Data written by Krishna Kumar Mohbey and published by . This book was released on 2020-12-09 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of the latest and representative developments in predictive analytics using big data technologies. It focuses on some critical aspects of big data and machine learning and provides studies for readers. The chapters address a comprehensive range of advanced data technologies used for statistical modeling towards predictive analytics.Topics included in this book include: - Categorized machine learning algorithms- Player monopoly in cricket teams.- Chain type estimators- Log type estimators- Bivariate survival data using shared inverse Gaussian frailty models- Weblog analysis- COVID-19 epidemiologyThis reference book will be of significant benefit to the predictive analytics community as a useful guide of the latest research in this emerging field