Federated Learning: Unlocking the Power of Collaborative Intelligence

本書透過詳細的案例研究和逐步實施指南，展示如何在現實世界的情境中建立和部署聯邦學習系統，例如在醫療保健、金融、物聯網和邊緣計算等領域。

M. Irfan Uddin is currently working as a faculty member at the Institute of Computing, Kohat University of Science and Technology, Kohat, Pakistan. He has received his academic qualifications in computer science and has worked as a researcher on funded projects. He is involved in teaching and research activities related to different diverse computer science topics and has more than 18 years of teaching plus research experience. He is a member of IEEE, ACM, and HiPEAC. He has organized national and international seminars, workshops, and conferences. He has published over a hundred research papers in international journals and conferences. His research interests include machine learning, data science, artificial neural networks, deep learning, convolutional neural networks, recurrent neural networks, attention models, reinforcement learning, generative adversarial networks, computer vision, image processing, machine translation, natural language processing, speech recognition, big data analytics, parallel programming, multi-core, many-core, and GPUs.

Wali Khan Mashwani received an M.Sc. degree in mathematics from the University of Peshawar, Khyber Pakhtunkhwa, Pakistan, in 1996, and a Ph.D. degree in mathematics from the University of Essex, UK, in 2012. He is currently a Professor of Mathematics and the Director of the Institute of Numerical Sciences, Kohat University of Science and Technology (KUST), Khyber Pakhtunkhwa. He is also a Dean of the Physical and Numerical Science faculty at KUST. He has published more than 100 academic papers in peer-reviewed international journals and conference proceedings. His research interests include evolutionary computation, hybrid evolutionary multi-objective algorithms, decomposition-based evolutionary methods for multi-objective optimization, mathematical programming, numerical analysis, and artificial neural networks.

M. Irfan Uddin 目前在巴基斯坦科哈特科技大學的計算機學院擔任教職。他在計算機科學領域獲得了學術資格，並曾在資助項目中擔任研究員。他參與與各種不同計算機科學主題相關的教學和研究活動，擁有超過18年的教學和研究經驗。他是 IEEE、ACM 和 HiPEAC 的成員，並組織過國內外的研討會、工作坊和會議。他在國際期刊和會議上發表了超過一百篇研究論文。他的研究興趣包括機器學習、數據科學、人工神經網絡、深度學習、卷積神經網絡、遞歸神經網絡、注意力模型、強化學習、生成對抗網絡、計算機視覺、圖像處理、機器翻譯、自然語言處理、語音識別、大數據分析、並行編程、多核心、許多核心和 GPU。

Wali Khan Mashwani 於1996年在巴基斯坦開伯爾省的白沙瓦大學獲得數學碩士學位，並於2012年在英國埃塞克斯大學獲得數學博士學位。他目前是科哈特科技大學（KUST）數值科學研究所的數學教授及所長，同時也是 KUST 物理與數值科學學院的院長。他在同行評審的國際期刊和會議論文集中發表了超過100篇學術論文。他的研究興趣包括進化計算、混合進化多目標算法、基於分解的多目標優化進化方法、數學規劃、數值分析和人工神經網絡。