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Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Sy
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Las opciones de envío
Estimado para llegar por Fri, Aug 15th.
Detalles
GRATIS a través de International Shipping (2 to 3 weeks) a Worldwide
Los buques de
India

Política de oferta
OBO - El vendedor acepta ofertas en este artículo.
Detalles
La política de devoluciones
Refunds available: See booth/item description for details
Protección de compra
Opciones de pago
PayPal accepted
PayPal Credit accepted
Venmo accepted
PayPal, MasterCard, Visa, Discover, and American Express accepted
Maestro accepted
Amazon Pay accepted
Nuvei accepted
Rasgos del artículo
Categoría: | |
---|---|
cantidad disponible: |
2 En stock |
Condition: |
Brand New |
ISBN: |
9781098107635 |
Format: |
Trade Paperback |
Type: |
Textbook |
Language: |
English |
Series: |
Addison-Wesley Professional Computing Ser. |
Subject Area: |
Mathematics/Computers |
Publication Name: |
Essential Math for AI: Next-Level Mathematics for Efficient and S |
Author: |
Hala Nelson |
Subject: |
Intelligence (Ai) & Semantics/General/Data Processing |
Detalles del anuncio
Envío de descuento: |
Vendedor paga el envío para este artículo. |
---|---|
Publicado en venta: |
Más de una semana |
Artículo número: |
1711225691 |
Descripción del Artículo
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Product Description
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
About the Author
Hala 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 University, she was a postdoctoral assistant professor at the University of Michigan, Ann Arbor. She specializes in mathematical modeling and consults for emergency and infrastructure services in the public sector. She likes to translate complex ideas into simple and practical terms. To her, most mathematical concepts are painless and relatable, unless the person presenting them either does not understand them very well, or is trying to show off. Other facts: Hala Nelson grew up in Lebanon during its brutal civil war. She lost her hair at a very young age in a missile explosion. This event, and many that followed, shaped her interests in human behavior, the nature of intelligence, and AI. Her dad taught her math, at home and in French, until she graduated high school. Her favorite quote from her dad about math is, ?It is the one clean science.?
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- Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Sy
- 2 in stock
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- Handling time 3 day. Estimated delivery: Fri, Aug 15th
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