Machine Learning. Supervised Learning with IBM SPSS Modeler PDF Download
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Author: F Marqués
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The goal of supervised machine learning is to build a model that makes evidence-based predictions in the presence of uncertainty. A supervised learning algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data. Supervised learning uses classification and regression techniques to develop predictive models. In this book, supervised learning Machine Learning techniques are developed and illustrated with full examples solved using the appropriate software. The IBM SPSS Modeler platform will be used, which is ideal for working with visual tools in all facets of Machine Learning.
Author: F Marqués
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The goal of supervised machine learning is to build a model that makes evidence-based predictions in the presence of uncertainty. A supervised learning algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data. Supervised learning uses classification and regression techniques to develop predictive models. In this book, supervised learning Machine Learning techniques are developed and illustrated with full examples solved using the appropriate software. The IBM SPSS Modeler platform will be used, which is ideal for working with visual tools in all facets of Machine Learning.
Author: F Marqués
Publisher: Independently Published
ISBN:
Category :
Languages : es
Pages : 0
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Book Description
El objetivo del aprendizaje automático supervisado es construir un modelo que haga predicciones basadas en evidencia en presencia de incertidumbre. Un algoritmo de aprendizaje supervisado toma un conjunto conocido de datos de entrada y respuestas conocidas a los datos (salida) y entrena un modelo para generar predicciones razonables para la respuesta a nuevos datos. El aprendizaje supervisado utiliza técnicas de clasificación y regresión para desarrollar modelos predictivos. En este libro se desarrollan técnicas de Machine Learning de aprendizaje supervisado y se ilustran con ejemplos total resueltos a partir del software adecuado para ello. Se utilizará la plataforma IBM SPSS Modeler ideal para trabajar con herramientas visuales en todas las facetas del Machine Learning.
Author: César Pérez López
Publisher:
ISBN: 9788419034076
Category :
Languages : es
Pages : 0
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Book Description
El libro está dirigido tanto a alumnos que siguen un Curso de especialización en Inteligencia Artificial y Big Data como a profesionales del sector.Comienza clasificando los sistemas, herramientas, técnicas y algoritmos o modelos aplicados al Aprendizaje Automático. A continuación, se tratan las técnicas de aprendizaje supervisado, sus fases y plataformas, así como los algoritmos y modelos más importantes. Se desarrollan las técnicas de regresión con sus fases de identificación, estimación, validación (diagnosis) y predicción.Se presentan los métodos especiales de regresión como PLS, LARS, LASSO, ELASTIC NET, RANSAC, THEIL, HUBERT, KERNEL RIDGE REGRESSION (KRR), SUPPORT VECTOR REGRESSION (SVR) y STOCHASTIC GRADIENT DESCENDT (SGD) entre otros.Asimismo, se tratan las técnicas de aprendizaje supervisado enfocadas a la clasificación o segmentación como los Modelos Logit y Probit, los Modelos Lineales Generalizados, los Árboles de Decisión, los Modelos de Análisis Discriminante, los Modelos SVM (Support Vector Machine), lo modelos kNN (Vecino más Cercano) y los Modelos SLRM (Respuesta de Autoaprendizaje).Todas las técnicas citadas anteriormente se ilustran con ejemplos y se resuelven con el software de Machine Learning adecuado, incluyendo Python, R, IBM SPSS Modeler y SAS Enterprise Miner.A continuación se abordan las técnicas de aprendizaje no supervisado como la Reducción de la Dimensión mediante Análisis de Componentes Principales y Análisis Factorial. Entre las técnicas de aprendizaje no supervisado para la clasificación y segmentación se desarrolla el Análisis Clúster tanto jerárquico como no jerárquico, algoritmos de detección de anomalías y Reglas de Asociación. Para todas las técnicas se presentan ejemplos significativos que se resuelven con el software más utilizado en estos casos, como R e IBM SPSS Modeler.Finalmente, se profundiza en los Modelos de Redes Neuronales, tanto para técnicas de aprendizaje supervisado como el ajuste de modelos predictivos (Perceptrón Multicapa y Red de Base Radial) como para técnicas de análisis no supervisado como el análisis clúster (Redes de Kohonen). Se desarrollan también las Redes Neuronales Bayesianas y se introducen las técnicas de Deep Learning y las Redes Neuronales Convolucionales. Se presentan ejemplos totalmente resueltos con software visual como es el caso de IBM SPSS Modeler. Se finaliza con las técnicas de valoración y comparación de modelos.
Author: Mohammed Serrhini
Publisher: Springer Nature
ISBN: 3030367789
Category : Technology & Engineering
Languages : en
Pages : 659
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Book Description
This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.
Author: Suresh Chandra Satapathy
Publisher: Springer
ISBN: 9811317429
Category : Technology & Engineering
Languages : en
Pages : 745
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Book Description
The book gathers papers addressing state-of-the-art research in all areas of Information and Communication Technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the third International Conference on Information and Communication Technology for Intelligent Systems, which was held on April 6–7, 2018, in Ahmedabad, India. Divided into two volumes, the book discusses the fundamentals of various data analytics and algorithms, making it a valuable resource for researchers’ future studies.
Author: Yen-Wei Chen
Publisher: Springer Nature
ISBN: 3030326063
Category : Technology & Engineering
Languages : en
Pages : 225
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Book Description
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
Author: Francesco Bandarin
Publisher: John Wiley & Sons
ISBN: 1119968097
Category : Architecture
Languages : en
Pages : 265
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Book Description
This book offers a comprehensive overview of the intellectual developments in urban conservation. The authors offer unique insights from UNESCO's World Heritage Centre and the book is richly illustrated with colour photographs. Examples are drawn from urban heritage sites worldwide from Timbuktu to Liverpool to demonstrate key issues and best practice in urban conservation today. The book offers an invaluable resource for architects, planners, surveyors and engineers worldwide working in heritage conservation, as well as for local authority conservation officers and managers of heritage sites.
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 1461463092
Category : Computers
Languages : en
Pages : 547
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Book Description
Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.
Author: Álvaro Rocha
Publisher: Springer Nature
ISBN: 9813341831
Category : Technology & Engineering
Languages : en
Pages : 783
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Book Description
This book includes selected papers presented at the International Conference on Marketing and Technologies (ICMarkTech 2020), held at ISCTE - University Institute of Lisbon, in the city of Lisbon in Portugal, between 8 and 10 October 2020. It covers up-to-date cutting-edge research on artificial intelligence applied in marketing, virtual and augmented reality in marketing, business intelligence databases and marketing, data mining and big data, marketing data science, web marketing, e-commerce and v-commerce, social media and networking, geomarketing and IoT, marketing automation and inbound marketing, machine learning applied to marketing, customer data management and CRM, and neuromarketing technologies.
Author: Pramod K. Nayar
Publisher: Springer
ISBN: 1137504323
Category : Political Science
Languages : en
Pages : 170
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Book Description
Set at the intersection of Human Rights, social justice and Literature, this cutting edge book examines a range of literary texts, fiction, plays and poetry, and through them considers representations of Human Rights and their violations. Examining violated bodies and subjects, the settings and environments in which these are embedded and the witnessing of atrocities, it considers how the ‘subject’ (or ‘person’ of Human Rights) emerges within fiction or poetry. Structured so as to move outward from the individual body to the world, the study progresses from the preconditions or settings for Human Rights violations through to atrocity, from witnessing to the making of a specific kind of public around traumatic recall. It addresses representations of destroyed corporeality and subjectivity, the violations and dissolution of the subject and the construction of trauma-memory citizenship to the making of communities of mourning. Through a broad study of texts from different genres, this text reveals how Literature both documents the basic human aspirations of happiness, security and hope, but also the limitations and the violations of these aspirations.
