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Math for Deep Learning - by Ronald T Kneusel (Paperback)
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Prompt Engineering for Llms - by John Berryman & Albert Ziegler (Paperback)
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High Performance Spark - 2nd Edition by Holden Karau & Adi Polak & Rachel Warren (Paperback)
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Natural Language Processing with Transformers, Revised Edition - by Lewis Tunstall & Leandro Von Werra & Thomas Wolf (Paperback)
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Cuda for Deep Learning - by Elliot Arledge (Paperback)
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Google Bigquery: The Definitive Guide - by Valliappa Lakshmanan & Jordan Tigani (Paperback)
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The Testability of Distributed Real-Time Systems - (The Springer International Engineering and Computer Science) by Werner Schütz (Hardcover)
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Dataproc Cookbook - by Narasimha Sadineni & Anuyogam Venkataraman (Paperback)
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Discrete Mathematics and Graph Theory - (Undergraduate Topics in Computer Science) by K Erciyes (Paperback)
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Beginning Salesforce Developer - by Michael Wicherski (Paperback)
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Machine Learning Design Patterns - by Valliappa Lakshmanan & Sara Robinson & Michael Munn (Paperback)
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Building Recommendation Systems in Python and Jax - by Bryan Bischof Ph D & Hector Yee (Paperback)
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Power BI - by Rob Botwright (Paperback)
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Algorithmic Realism - by Ben Green (Paperback)
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Llms and Generative AI for Healthcare - by Kerrie Holley & Manish Mathur (Paperback)
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Tiny Machine Learning: Design Principles and Applications - by Agbotiname Lucky Imoize & Dinh-Thuan Do & Houbing Herbert Song (Hardcover)
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Engineering Lakehouses with Open Table Formats - by Dipankar Mazumdar & Vinoth Govindarajan (Paperback)
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Practical Salesforce Development Without Code - 2nd Edition by Philip Weinmeister (Paperback)
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