Angol
Natural Language Processing (NLP) is often regarded as a cornerstone of artificial intelligence. The advent of deep learning has revolutionized NLP techniques, particularly with the rise of large language models in recent years, which have established a new paradigm for NLP research. This book introduces fundamental concepts in natural language processing and deep learning while emphasizing modern NLP techniques driven by pre-trained and large language models.
The book is structured into three main sections:
Beyond theoretical foundations, this book incorporates practical case studies with accompanying PyTorch code implementations, enabling readers to deepen their understanding while seamlessly applying NLP models in practice-bridging theory with hands-on experience.
Designed for college students, academic researchers, and computer engineers with a basic knowledge of machine learning, this book serves as a valuable resource for those seeking to advance their expertise in NLP algorithms. It is also an essential reference for students and professionals interested in artificial intelligence, deep learning, large language models, and natural language processing, as well as individuals aspiring to enter the field of AI applications.
