Silipo, Silipo (123 results)

Paperback. Condition: Very Good. Catalogue of the Pucker Gallery show held on March 31 to April 30, 2012 for ceramic works by Young-jae Lee. Binding firm, interior clean and unmarked. Cover has light edge wear o/w Very Good.

Hardcover. Condition: Very Good. Dust Jacket Condition: Published Without Dust Jacket. 243 pp. Tightly bound. Corners not bumped. NOTE: Lightly bumped at the head of the spine. Text is free of markings. No ownership markings. Published without dust jacket. Printed boards.

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Condition: BUONO. NOTA:Aloni e ebruniture alla copertina. Etichetta d'appartenenza al dorso del volume. / Torino, SEI-Società Editrice Internazionale cm.13x18, pp.278, brossura.

Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

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Paperback. Condition: Very Good. Unmarked. Color reproductions highlighting landscapes. Includes a conversation between S. Lane Faison, Jr., Professor Emeritus of Art History at Williams College and Stephen Hannock, an artist, on the subject of landscape painting. Other artists include Gracia Dayton, Chet Kalm, John MacDonald, Tjasa, Bill Shattuck, Pamela Simpson, John Terelak, and Mary Sipp Green. 32p.…

Condition: BUONO USATO. Da revisionare INGLESE Numerosi gli autori che hanno contribuito alla stesura del testo. Volume inerente le banche e l'economia italiana. Introduzione a cura di Damiano Bruno Silipo, Professore del dipartimento di economia e statistica dell'università della Calabria. Legatura leggermente stanca agli angoli e al piede del dorso. Pagine ben salde alla cerniera, con ampio margine. Numero pagine 243.…

In-8°, pp. 32. Bross. edit. illustrata. Tracce del tempo e bruniture sui piatti, diffuso ingiallimento sulle pagine. Piccola ininfluente mancanza nel margine inferiore del piatto anteriore.

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Paperback. Condition: New. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutionsKey FeaturesBecome well-versed with KNIME Analytics Platform to perform codeless deep learningDesign and build deep learning workflows quickly and more easily using the KNIME GUIDiscover different deployment options without using a single line of code with KNIME Analytics PlatformBook DescriptionKNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It'll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you'll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You'll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you'll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you'll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.What you will learnUse various common nodes to transform your data into the right structure suitable for training a neural networkUnderstand neural network techniques such as loss functions, backpropagation, and hyperparametersPrepare and encode data appropriately to feed it into the networkBuild and train a classic feedforward networkDevelop and optimize an autoencoder network for outlier detectionImplement deep learning networks such as CNNs, RNNs, and LSTM with the help of practical examplesDeploy a trained deep learning network on real-world dataWho this book is forThis book is for data analysts, data scientists, and deep learning developers who are not well-versed in Python but want to learn how to use KNIME GUI to build, train, test, and deploy neural networks with different architectures. The practical implementations shown in the book do not require coding or any knowledge of dedicated scripts, so you can easily implement your knowledge into practical applications. No prior experience of using KNIME is required to get started with this book.…

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rilegato. Condition: Good. 0. Copertina plastificata. Tagli e pagine integri. 9783790821116 Buono (Good) . Book.

Brossura. Condition: new. Roma, 2020; br., pp. 48. "Siamo pedine bianche e nere,gli alfieri di due scacchiere,non giocheremo mai la stessa partita,ma non è detto che sia finita."Una scacchiera, quella della vita, dove siamo tutti pedine, tutte con lo stesso destino, re o cavallo non cambia, bianche o nere non cambia.È su questa scacchiera che si prende consapevolezza di se stessi e degli altri. L'autore comprende e trasmette il messaggio che non si è soli in questo mondo; che in qualche posto ci aspetta qualcuno pronto ad amarci e pronto a sostenerci nelle scelte in cui l'ultima mossa tocca sempre a noi. (Fondazione Mario Luzi - marioluzi.it). Libro.…

Paperback. Condition: New.

Paperback. Condition: New.

Paperback. Condition: New. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutionsKey FeaturesBecome well-versed with KNIME Analytics Platform to perform codeless deep learningDesign and build deep learning workflows quickly and more easily using the KNIME GUIDiscover different deployment options without using a single line of code with KNIME Analytics PlatformBook DescriptionKNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It'll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you'll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You'll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you'll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you'll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.What you will learnUse various common nodes to transform your data into the right structure suitable for training a neural networkUnderstand neural network techniques such as loss functions, backpropagation, and hyperparametersPrepare and encode data appropriately to feed it into the networkBuild and train a classic feedforward networkDevelop and optimize an autoencoder network for outlier detectionImplement deep learning networks such as CNNs, RNNs, and LSTM with the help of practical examplesDeploy a trained deep learning network on real-world dataWho this book is forThis book is for data analysts, data scientists, and deep learning developers who are not well-versed in Python but want to learn how to use KNIME GUI to build, train, test, and deploy neural networks with different architectures. The practical implementations shown in the book do not require coding or any knowledge of dedicated scripts, so you can easily implement your knowledge into practical applications. No prior experience of using KNIME is required to get started with this book.…

Paperback. Condition: New. Second Edition 2020. Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of thesubject.…