GPU-Accelerated Deep Learning: Essential Gpu Ideas, Deep Learning Frameworks, and Optimization Approaches
暫譯: GPU 加速深度學習：基本 GPU 概念、深度學習框架與優化方法
Mangrulkar, Ramchandra S., Chavan, Pallavi Vijay
- 出版商: Apress
- 出版日期: 2025-12-17
- 售價: $2,400
- 貴賓價: 9.5 折 $2,280
- 語言: 英文
- 頁數: 146
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798868820823
- ISBN-13: 9798868820823
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
Explore the convergence of deep learning and GPU technology. This book is a complete guide for those wishing to use GPUs to accelerate AI workflows.
The book is meant to make complex concepts understandable, with step-by-step instructions on how to set up and use GPUs in deep learning applications. Starting with an introduction to the fundamentals, you'll dive into progressive topics like Convolutional Neural Networks (CNNs) and sequence models, exploring how GPU optimization boosts performance. Further, you will learn the power of generative models, and take your skills by deploying AI models on edge devices. Finally, you will master the art of scaling and distributed training to handle large datasets and complex tasks efficiently.
This book is your roadmap to becoming proficient in deep learning and harnessing the full potential of GPUs.
What You Will Learn:
- How to apply deep learning techniques on GPUs to solve challenging AI problems.
- Optimizing neural networks for faster training and inference on GPUs
- Integration of GPUs with Microsoft Copilots
- Implementing VAEs (Variational Autoencoders) with TensorFlow and PyTorch
Who This Book Is For:
Industry IT professionals in AI. Students pursuing undergraduate and postgraduate degrees in Engineering, Computer Science, Data Science.
商品描述(中文翻譯)
探索深度學習與GPU技術的融合。本書是希望利用GPU加速AI工作流程的完整指南。
本書旨在使複雜的概念變得易於理解，提供逐步的指導，教您如何在深度學習應用中設置和使用GPU。從基礎知識的介紹開始，您將深入探討逐步進階的主題，如卷積神經網絡（Convolutional Neural Networks, CNNs）和序列模型，探索GPU優化如何提升性能。此外，您將學習生成模型的強大功能，並通過在邊緣設備上部署AI模型來提升您的技能。最後，您將掌握擴展和分佈式訓練的藝術，以有效處理大型數據集和複雜任務。
本書是您成為深度學習專家並充分利用GPU潛力的路線圖。
您將學到的內容：
- 如何在GPU上應用深度學習技術以解決具有挑戰性的AI問題。
- 優化神經網絡以實現更快的訓練和推理。
- GPU與Microsoft Copilots的整合。
- 使用TensorFlow和PyTorch實現變分自編碼器（Variational Autoencoders, VAEs）。
本書適合對象：
從事AI的行業IT專業人士。追求工程、計算機科學、數據科學本科及研究生學位的學生。
作者簡介
Dr. Ramchandra Sharad Mangrulkar is a Professor in the Department of Information Technology at Dwarkadas J. Sanghvi College of Engineering in Mumbai, India. He holds various memberships in professional organizations such as IEEE, ISTE, ACM, and IACSIT. He completed his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from S.G.B. Amravati University in Maharashtra, and Master of Technology (MTech) degree in Computer Science and Engineering from the National Institute of Technology, Rourkela. Dr. Mangrulkar is proficient in several technologies and tools, including Microsoft's Power BI, Power Automate, Power Query, Power Virtual Agents, Google's Dialog Flow, and Overleaf. With over 23 years of combined teaching and administrative experience, Dr. Mangrulkar has established himself as a knowledgeable and skilled professional in his field. He has also obtained certifications such as Certified Network Security Specialist (ICSI - CNSS) from ICSI, UK. Dr. Mangrulkar has a strong publication record with 95 publications including refereed/peer-reviewed international journal publications, book chapters with international publishers (including Scopus indexed ones), and international conference publications.
Dr. Pallavi Vijay Chavan is an Associate Professor in the Department of Information Technology at Ramrao Adik Institute of Technology, D Y Patil Deemed to be University, Navi Mumbai, MH, India. She has been in academics since the past 17 years and has worked in the areas of computing theory, data science, and network security. In her academic journey, she has published research work in the data science and security domains with reputed publishers including Springer, Elsevier, CRC Press, and Inderscience. She has published 2 books, 7+ book chapters, 10+ international journal papers and 30+ international conference papers. She is currently guiding 5 Ph.D. research scholars. She completed her Ph.D. from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur, MH, India in 2017. She secured the first merit position in Nagpur University for the degree of B.E. in Computer Engineering in 2003. She is recipient of research grants from UGC, CSIR, and University of Mumbai. She is an active reviewer for Elsevier and Inderscience journals. Her firm belief is "Teaching is a mission."
作者簡介(中文翻譯)
Dr. Ramchandra Sharad Mangrulkar 是印度孟買 Dwarkadas J. Sanghvi 工程學院資訊科技系的教授。他是多個專業組織的成員，包括 IEEE、ISTE、ACM 和 IACSIT。他在馬哈拉施特拉邦的 S.G.B. Amravati 大學獲得計算機科學與工程的哲學博士（Ph.D.）學位，並在國立技術學院 Rourkela 獲得計算機科學與工程的技術碩士（MTech）學位。Dr. Mangrulkar 精通多種技術和工具，包括微軟的 Power BI、Power Automate、Power Query、Power Virtual Agents、谷歌的 Dialog Flow 和 Overleaf。擁有超過 23 年的教學和行政經驗，Dr. Mangrulkar 在其領域內建立了豐富的知識和技能。他還獲得了來自英國 ICSI 的認證網絡安全專家（ICSI - CNSS）資格。Dr. Mangrulkar 擁有強大的出版記錄，共有 95 篇出版物，包括經過審核的國際期刊文章、與國際出版商（包括 Scopus 索引的出版商）合作的書籍章節，以及國際會議的出版物。
Dr. Pallavi Vijay Chavan 是印度 Navi Mumbai D Y Patil 被認可大學 Ramrao Adik 技術學院資訊科技系的副教授。她在學術界已有 17 年，並在計算理論、數據科學和網絡安全等領域工作。在她的學術旅程中，她在數據科學和安全領域發表了多篇研究作品，與知名出版商如 Springer、Elsevier、CRC Press 和 Inderscience 合作。她已出版 2 本書、7 篇以上的書籍章節、10 篇以上的國際期刊論文和 30 篇以上的國際會議論文。她目前指導 5 位博士研究生。她於 2017 年在印度 Nagpur 的 Rashtrasant Tukadoji Maharaj Nagpur 大學獲得博士學位。她在 2003 年獲得 Nagpur 大學計算機工程學士學位時，名列第一。她曾獲得 UGC、CSIR 和孟買大學的研究資助。她是 Elsevier 和 Inderscience 期刊的活躍審稿人。她堅信「教學是一項使命。」
