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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Original o primera edición
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Añadir al carritoCondición: New. 2020. 1st Edition. Hardback. . . . . .
Librería: moluna, Greven, Alemania
EUR 216,78
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Añadir al carritoGebunden. Condición: New. Uma N. Dulhare is a Professor in the Department of Computer Science & Eng., MJCET affiliated to Osmania University, Hyderabad, India. She has more than 20 years teaching experience years with many publications in reputed international conferences, journals .
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 280,01
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 293,40
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Añadir al carritoHardcover. Condición: Brand New. 512 pages. 9.00x6.00x1.25 inches. In Stock.
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EUR 317,76
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Añadir al carritoCondición: New. 2020. 1st Edition. Hardback. . . . . . Books ship from the US and Ireland.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 303,60
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Añadir al carritoBuch. Condición: Neu. Neuware - This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations.The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems.Subjects covered in detail include:\* Mathematical foundations of machine learning with various examples.\* An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview.\* Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth.\* Hands-on machine leaning open source tools viz. Apache Mahout, H2O.\* Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning.\* Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Idioma: Inglés
Publicado por John Wiley & Sons Inc, New York, 2020
ISBN 10: 1119654742 ISBN 13: 9781119654742
Librería: CitiRetail, Stevenage, Reino Unido
EUR 251,45
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Añadir al carritoHardcover. Condición: new. Hardcover. This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples.An empirical study of supervised learning algorithms like Naive Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview.Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth.Hands-on machine leaning open source tools viz. Apache Mahout, H2O.Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning.Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 288,60
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Añadir al carritoHardcover. Condición: Brand New. 512 pages. 9.00x6.00x1.25 inches. In Stock. This item is printed on demand.