Deep Learning for Natural Language Processing: A Gentle Introduction

Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.

深度學習在科技主導的世界中變得越來越重要。然而，建立準確代表語言結構的計算模型是復雜的，因為它涉及對神經網絡的深入了解，以及對微積分和統計等高級數學概念的理解。本書通過清晰介紹自然語言處理的深度學習，使這些複雜性對人文和社會科學背景的讀者易於理解。它涵蓋了理論和實踐兩個方面，並假設讀者對機器學習的知識很少，以易讀的方式解釋自然語言背後的理論。它包括了簡單算法的偽代碼，以及較複雜架構的實際Python代碼，使用現代深度學習庫，如PyTorch和Hugging Face。本書提供了必要的理論基礎和實用工具，讓讀者能夠立即開始構建實際的自然語言處理系統。