Mathematical Foundations for Deep Learning
暫譯: 深度學習的數學基礎
Ghayoumi, Mehdi
- 出版商: CRC
- 出版日期: 2025-08-05
- 售價: $5,650
- 貴賓價: 9.5 折 $5,368
- 語言: 英文
- 頁數: 374
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032690739
- ISBN-13: 9781032690735
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
Mathematical Foundations for Deep Learning bridges the gap between theoretical mathematics and practical applications in artificial intelligence. This guide delves into the fundamental mathematical concepts that power modern deep learning, equipping readers with the tools and knowledge needed to excel in the rapidly evolving field of AI.
Designed for learners at all levels, from beginners to experts, the book makes mathematical ideas accessible through clear explanations, real-world examples, and targeted exercises. Readers will master core concepts in linear algebra, calculus, and optimization techniques, understand the mechanics of deep learning models, and apply theory to practice using frameworks like TensorFlow and PyTorch.
By integrating theory with practical application, Mathematical Foundations for Deep Learning prepares you to navigate the complexities of AI confidently. Whether you're aiming to develop practical skills for AI projects, advance to emerging trends in deep learning, or lay a strong foundation for future studies, this book serves as an indispensable resource for achieving proficiency in the field.
Embark on an enlightening journey that fosters critical thinking and continuous learning. Invest in your future with a solid mathematical base, reinforced by case studies and applications that bring theory to life, and gain insights into the future of deep learning.
商品描述(中文翻譯)
《深度學習的數學基礎》彌合了理論數學與人工智慧實際應用之間的鴻溝。本指南深入探討了驅動現代深度學習的基本數學概念,為讀者提供在快速發展的人工智慧領域中脫穎而出的工具和知識。
本書針對各個層級的學習者設計,從初學者到專家,通過清晰的解釋、真實的案例和針對性的練習,使數學思想變得易於理解。讀者將掌握線性代數、微積分和優化技術的核心概念,理解深度學習模型的運作機制,並使用如 TensorFlow 和 PyTorch 等框架將理論應用於實踐。
通過將理論與實際應用相結合,《深度學習的數學基礎》使您能夠自信地應對人工智慧的複雜性。無論您是希望為人工智慧項目發展實用技能、跟上深度學習的新興趨勢,還是為未來的學習奠定堅實基礎,本書都是您在該領域達到精通的不可或缺的資源。
展開一段啟發性的旅程,培養批判性思維和持續學習的能力。以堅實的數學基礎投資您的未來,通過案例研究和應用使理論生動化,並獲得對深度學習未來的洞察。
作者簡介
Dr. Mehdi Ghayoumi is an Assistant Professor at the Center for Criminal Justice, Intelligence, and Cybersecurity at SUNY Canton, recognized for his excellence in teaching and research--including previous roles at SUNY Binghamton and Kent State University, where he received consecutive Teaching Awards in 2016 and 2017. His multidisciplinary research focuses on machine learning, robotics, human-robot interaction, and privacy, aiming to develop practical systems for real-world applications in manufacturing, biometrics, and healthcare. Actively contributing to the academic community, Dr. Ghayoumi develops courses in emerging technologies and serves on technical program committees and editorial boards for leading conferences and journals in his field.
作者簡介(中文翻譯)
梅赫迪·蓋尤米博士是紐約州立大學坎頓分校刑事司法、情報與網路安全中心的助理教授,以其卓越的教學和研究而聞名。他曾在紐約州立大學賓漢頓分校和肯特州立大學擔任職務,並於2016年和2017年連續獲得教學獎。他的多學科研究專注於機器學習、機器人技術、人機互動和隱私,旨在為製造、生物識別和醫療保健等現實應用開發實用系統。蓋尤米博士積極貢獻於學術社群,開發新興技術課程,並擔任其領域內主要會議和期刊的技術程序委員會和編輯委員會成員。