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[null,"1.","Record Nr.",null,"UNINA9910795406803321"]
[null,null,"Autore",null,"Faïz Latéfa"]
[null,null,"Titolo",null,"Yves Saint Laurent : el visionario que transforma la moda del siglo XX / / por Latéfa Faïz ; traducido por Laura Bernal Martín"]
[null,null,"Pubbl/distr/stampa",null,"España : , : 50Minutos.es, , 2018"]
[null,null,"ISBN",null,"2-8080-0408-7"]
[null,null,"Descrizione fisica",null,"1 recurso electrónico (41 páginas) : ilustraciones"]
[null,null,"Collana",null,"Historia"]
[null,null,"Disciplina",null,"746.92092"]
[null,null,"Soggetti",null,"Diseñadores de moda"]
[{"$nulls":4},"Libros electrónicos"]
[null,null,"Lingua di pubblicazione",null,"Spagnolo"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Este libro es una guía práctica y accesible para saber más sobre Yves Saint Laurent, que le aportará la información esencial y le permitirá ganar tiempo. En tan solo 50 minutos, usted podrá: * Descubrir la vida y obra de Yves Saint Laurent, el célebre modisto francés que transforma para siempre los códigos vestimentarios masculinos y femeninos  * Profundizar en los momentos clave de su vida, marcada por el trauma que supone su paso obligado por las filas del ejército francés para luchar en la guerra de Argelia, o la apertura de la casa Yves Saint Laurent * Conocer sus fuentes de inspiración, como Mondrian o Picasso, y las repercusiones de su manera de concebir la moda, que derivan en la transformación de los códigos de vestimenta masculinos y femeninos SOBRE 50MINUTOS.ES | Historia 50MINUTOS.ES le ofrece las claves para entender rápidamente los principales acontecimientos históricos que cambiaron el mundo.  Nuestras obras narran de forma rápida y eficaz una gran variedad de acontecimientos históricos clave de distintas épocas, desde la Antigua Grecia hasta la caída del muro de Berlín. ¡Descubra en un tiempo récord la historia que ha marcado el rumbo del mundo!"]
[null,"2.","Record Nr.",null,"UNINA9910838222203321"]
[null,null,"Autore",null,"Ilyas Ihab F"]
[null,null,"Titolo",null,"Data Cleaning"]
[null,null,"Pubbl/distr/stampa",null,"San Rafael : , : Morgan & Claypool Publishers, , 2019"]
[{"$nulls":4},"©2019"]
[null,null,"ISBN",null,"1-4503-7155-8"]
[null,null,"Descrizione fisica",null,"1 online resource (284 pages)"]
[null,null,"Disciplina",null,"005.74"]
[null,null,"Soggetti",null,"Data editing"]
[{"$nulls":4},"Database management"]
[{"$nulls":4},"Electronic data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Contents -- Preface -- Figure and Table Credits -- 1. Introduction -- 2. Outlier Detection -- 3. Data Deduplication -- 4. Data Transformation -- 5. Data Quality Rule Definition and Discovery -- 6. Rule-Based Data Cleaning -- 7. Machine Learning and Probabilistic Data Cleaning -- 8. Conclusion and Future Thoughts -- References -- Index -- Author Biographies -- Blank Page."]
[null,null,null,"Sommario/riassunto","This is an overview of the end-to-end data cleaning process. Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions. Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems. This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, this book describes various error detection and repair methods, and attempts to anchor these proposals with multiple taxonomies and views. Specifically, it covers four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, it includes a chapter that specifically "]
[{"$nulls":4},"explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models. This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate."]