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Paperback or Softback. Condizione: New. Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems. Book.
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Aggiungi al carrelloPaperback. Condizione: New. Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field.Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and moreLearn how to adapt mathematical methods to different applications from completely different fieldsGain the mathematical fluency to interpret and explain how AI systems arrive at their decisions.
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Aggiungi al carrelloPaperback. Condizione: USED BOOKS. Used Books ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 50,71
Quantità: 5 disponibili
Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2023
ISBN 10: 1098107632 ISBN 13: 9781098107635
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI-including regression, neural networks, optimization, backpropagation, and Markov chains. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Aggiungi al carrelloCondizione: New. 2023. Paperback. . . . . .
Da: Majestic Books, Hounslow, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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EUR 77,94
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Aggiungi al carrelloPaperback. Condizione: New. Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field.Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and moreLearn how to adapt mathematical methods to different applications from completely different fieldsGain the mathematical fluency to interpret and explain how AI systems arrive at their decisions.
Condizione: New. 2023. Paperback. . . . . . Books ship from the US and Ireland.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 61,69
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 84,83
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EUR 51,15
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Da: Revaluation Books, Exeter, Regno Unito
EUR 82,22
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Aggiungi al carrelloPaperback. Condizione: Brand New. 425 pages. 9.19x7.00x1.30 inches. In Stock.
Paperback. Condizione: New. Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field.Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and moreLearn how to adapt mathematical methods to different applications from completely different fieldsGain the mathematical fluency to interpret and explain how AI systems arrive at their decisions.
Da: moluna, Greven, Germania
EUR 61,74
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Aggiungi al carrelloCondizione: New. Über den AutorHala Nelson is an Associate Professor of Mathematics at James Madison University. She has a Ph.D. in mathematics from the Courant Institute of Mathematical Sciences at New York University. Prior to James Madison Univer.
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2023
ISBN 10: 1098107632 ISBN 13: 9781098107635
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 104,34
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI-including regression, neural networks, optimization, backpropagation, and Markov chains. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.