Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
EUR 21,00
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Aggiungi al carrelloXII, 360 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Computational Intelligence, 865. Sprache: Englisch.
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Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
EUR 64,03
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Aggiungi al carrelloCondizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 55,24
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 55,24
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Da: BOOKWEST, Phoenix, AZ, U.S.A.
EUR 44,57
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Aggiungi al carrelloSoft cover. Condizione: New. US SELLER SHIPS FROM USA.
Editore: Springer International Publishing, 2021
ISBN 10: 3031037480 ISBN 13: 9783031037481
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,84
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning toaddress a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.
Editore: Springer International Publishing, 2023
ISBN 10: 3031303954 ISBN 13: 9783031303951
Lingua: Inglese
Da: Buchpark, Trebbin, Germania
Condizione: Gut. Zustand: Gut | Seiten: 192 | Sprache: Englisch | Produktart: Bücher.
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Da: suffolkbooks, Center moriches, NY, U.S.A.
EUR 24,26
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Aggiungi al carrellopaperback. Condizione: Very Good. Fast Shipping - Safe and Secure 7 days a week!
Da: Book Dispensary, Concord, ON, Canada
EUR 75,79
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Aggiungi al carrelloHardcover. Condizione: Very Good. VERY GOOD hardcover, no marks in text, very clean exterior, appears unread. Book.
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Editore: LAP LAMBERT Academic Publishing Apr 2024, 2024
ISBN 10: 6207487907 ISBN 13: 9786207487905
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 79,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -A book that covers different machine learning and deep learning algorithms specifically for lung cancer would be an excellent resource for researchers, medical professionals, and data scientists interested in leveraging artificial intelligence for medical diagnosis and treatment. While I can't provide a specific book title, I can suggest the key topics and areas such a book might cover: Introduction to Lung Cancer: The book may start with an overview of lung cancer, including its types, causes, diagnosis methods, and current treatment options. Machine Learning Fundamentals: It may cover fundamental concepts of machine learning, including supervised, unsupervised, and semi-supervised learning, as well as evaluation metrics commonly used in medical applications.Data Preprocessing and Feature Engineering: The book may discuss techniques for preprocessing medical imaging data, such as CT scans or X-rays, including image normalization, noise reduction, and feature extraction.Classification Algorithms: It would likely delve into various classification algorithms used for lung cancer detection and diagnosis, such as support vector machines (SVM), random forests, decision trees.Books on Demand GmbH, Überseering 33, 22297 Hamburg 184 pp. Englisch.
Da: HPB-Red, Dallas, TX, U.S.A.
EUR 17,59
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Aggiungi al carrellopaperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Editore: Beijing Institute of Technology Press, 2023
ISBN 10: 7576323051 ISBN 13: 9787576323054
Lingua: Inglese
Da: liu xing, Nanjing, JS, Cina
EUR 110,85
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Aggiungi al carrellopaperback. Condizione: New. Language:Chinese.Paperback.Pub Date:2023-04 Pages:316 Publisher:Beijing Institute of Technology Press Deep Learning and Computer Vision: Core Algorithms and Applications combines theory with practice. and introduces in detail the commonly used algorithms and models of machine learning and deep learning and their typical applications in the field of computer vision. For beginners. this book systematically introduces the modeling process and methods from scratch. which can lead them to get star.
Da: Books Puddle, New York, NY, U.S.A.
EUR 119,77
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Aggiungi al carrelloCondizione: New. pp. 270.
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Da: Lacey Books Ltd, Cirencester, Regno Unito
EUR 102,93
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Aggiungi al carrelloPaperback. Condizione: Very Good. 2022 Springer paperback edition. Unread copy in very good condition.
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Editore: Springer-Nature New York Inc, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 140,69
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Aggiungi al carrelloHardcover. Condizione: Brand New. 2nd edition. 242 pages. 9.25x6.10x9.21 inches. In Stock.
Editore: World Scientific Publishing Company, 2024
ISBN 10: 9811286485 ISBN 13: 9789811286483
Lingua: Inglese
Da: California Books, Miami, FL, U.S.A.
EUR 167,63
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 168,58
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 181,17
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 181,17
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Editore: Springer International Publishing, Springer International Publishing, 2024
ISBN 10: 3031185544 ISBN 13: 9783031185540
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 192,59
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study.The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice.The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 206,36
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 216,40
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 256,73
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