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Machine Learning Data Science Fundamentals by Prateek Agrawal Charu Gupta Anand (9 results)
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hardcover. Condition: 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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Machine Learning And Data Science: Fundamentals And Applications
Published by John Wiley, 2022
Language: English
Hardcover. Condition: New. ISBN:9781119775614.
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Machine Learning and Data Science: Fundamentals and Applications
Published by John Wiley & Sons Inc, 2022
ISBN 10: 1119775612 ISBN 13: 9781119775614
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
Condition: New. 2021. 1st Edition. Hardcover. . . . . .
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Condition: New. pp. 350.
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Gebunden. Condition: New. Prateek Agrawal, PhD, completed his BTech in computer science engineering from Uttar Pradesh Technical University, Lucknow, India and MTech from ABV-IIITM, Gwalior, India. He also received his PhD from IKG-Punjab Technical University, Punjab, India. He has .
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Condition: New. pp. 350.
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Machine Learning and Data Science: Fundamentals and Applications
Published by John Wiley & Sons Inc, 2022
ISBN 10: 1119775612 ISBN 13: 9781119775614
Language: English
Condition: New. 2021. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
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Hardcover. Condition: Brand New. 350 pages. 0.39x0.39x0.39 inches. In Stock.
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Buch. Condition: Neu. Neuware - MACHINE LEARNING AND DATA SCIENCEWritten and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.
