Transformers for Machine Learning: A Deep Dive
暫譯: 機器學習中的變壓器：深入探討

變壓器（Transformers）正逐漸成為許多神經網絡架構的核心部分，應用於自然語言處理（NLP）、語音識別、時間序列和計算機視覺等廣泛的應用領域。變壓器經歷了許多適應和改變，產生了更新的技術和方法。本書是關於變壓器的第一本綜合性著作。

Uday Kamath has spent more than two decades developing analytics products and combines this experience with learning in statistics, optimization, machine learning, bioinformatics, and evolutionary computing. Uday has contributed to many journals, conferences, and books, is the author of books like XAI: An Introduction to Interpretable XAI, Deep Learning for NLP and Speech Recognition, Mastering Java Machine Learning, and Machine Learning: End-to-End guide for Java developers. He held many senior roles: Chief Analytics Officer for Digital Reasoning, Advisor for
Falkonry, and Chief Data Scientist for BAE Systems Applied Intelligence. Uday has many patents and has built commercial products using AI in domains such as compliance, cybersecurity, financial crime, and bioinformatics. Uday currently works as the Chief Analytics Officer for Smarsh. He is responsible for data science, research of analytical products employing deep learning, transformers, explainable AI, and modern techniques in speech and text for the financial domain and healthcare.

Wael Emara has two decades of experience in academia and industry. Wael has a PhD in Computer Engineering and Computer Science with emphasis on machine learning and artificial intelligence. His technical background and research spans signal and image processing, computer vision, medical imaging, social media analytics, machine learning, and natural language processing. Wael has 10 research publications in various machine learning topics and he is active in the technical community in the greater New York area. Wael currently works as a Senior Research Engineer for Digital Reasoning where he is doing research on state-of-the-art artificial intelligence NLP systems.

Kenneth L. Graham has two decades experience solving quantitative problems in multiple domains, including Monte Carlo simulation, NLP, anomaly detection, cybersecurity, and behavioral profiling. For the past nine years, he has focused on building scalable solutions in NLP for government and industry, including entity coreference resolution, text classification, active learning, and temporal normalization. Kenneth currently works at Smarsh as a Principal Research Engineer, researching how to move state-of the-art NLP methods out of research and into production. Kenneth has five patents for his work in natural language processing, seven research publications, and a Ph.D. in Condensed Matter Physics.

Uday Kamath 擁有超過二十年的分析產品開發經驗，並將這些經驗與統計學、優化、機器學習、生物資訊學和演化計算的學習相結合。Uday 曾為許多期刊、會議和書籍做出貢獻，並著有《XAI: An Introduction to Interpretable XAI》、《Deep Learning for NLP and Speech Recognition》、《Mastering Java Machine Learning》和《Machine Learning: End-to-End guide for Java developers》等書籍。他曾擔任多個高級職位，包括 Digital Reasoning 的首席分析官、Falkonry 的顧問，以及 BAE Systems Applied Intelligence 的首席數據科學家。Uday 擁有多項專利，並在合規性、網絡安全、金融犯罪和生物資訊學等領域利用人工智慧構建商業產品。Uday 目前擔任 Smarsh 的首席分析官，負責數據科學、深度學習、變壓器、可解釋的人工智慧以及金融領域和醫療保健中語音和文本的現代技術的分析產品研究。

Wael Emara 擁有二十年的學術和產業經驗。Wael 擁有計算機工程和計算機科學的博士學位，專注於機器學習和人工智慧。他的技術背景和研究涵蓋信號和影像處理、計算機視覺、醫療影像、社交媒體分析、機器學習和自然語言處理。Wael 在各種機器學習主題上發表了 10 篇研究論文，並在大紐約地區的技術社群中活躍。Wael 目前擔任 Digital Reasoning 的高級研究工程師，從事最先進的人工智慧自然語言處理系統的研究。

Kenneth L. Graham 擁有二十年的經驗，解決多個領域的定量問題，包括蒙地卡羅模擬、自然語言處理、異常檢測、網絡安全和行為分析。在過去的九年中，他專注於為政府和產業構建可擴展的自然語言處理解決方案，包括實體共指解析、文本分類、主動學習和時間標準化。Kenneth 目前在 Smarsh 擔任首席研究工程師，研究如何將最先進的自然語言處理方法從研究轉移到生產中。Kenneth 擁有五項自然語言處理方面的專利、七篇研究論文，以及凝聚態物理的博士學位。