Natural Language Processing with PyTorch

□ I. THÔNG TIN SẢN PHẨM
□ Mã sản phẩm : STT1745
□ Nhà xuất bản : O'Reilly Media
□ Tác giả : Delip Rao & Brian McMahan
□ Ngôn ngữ : Tiếng Anh
□ ISBN : 9781491978238
□ Số trang : 254 trang
□ Hình thức : Bìa Mềm, RUỘT IN ĐEN TRẮNG, BÌA IN MẪU LASER GIẤY C300 CÓ CÁN
□ Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
□ Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và highlight thoải mái.
□ Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

□ II. MÔ TẢ SẢN PHẨM
□ 1.Mô tả sản phẩm đầy đủ
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahan provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. The book is structured to take you from the very basics of PyTorch to advanced architectures. Each chapter includes several code examples and illustrations to help you grasp complex concepts. You will begin by exploring computational graphs and the supervised learning paradigm, which are the bedrock of modern deep learning. From there, the authors guide you through the PyTorch optimized tensor manipulation library, ensuring you can efficiently handle the numerical computations required for AI models. As you progress, you will get an overview of traditional NLP concepts and methods, bridging the gap between classic linguistics and modern neural approaches. The book delves into building neural networks from scratch and using embeddings to represent words, sentences, documents, and other features. These embeddings are crucial for capturing semantic meaning. PyTorch's dynamic nature makes it an ideal choice for NLP, where input lengths vary and flexibility is key. This book highlights how PyTorch’s ecosystem simplifies data preprocessing and model evaluation. Advanced topics include sequence prediction and the generation of sequence-to-sequence models, essential for tasks like machine translation. Finally, the book covers design patterns for building production-ready NLP systems, moving beyond academic exercises to real-world deployment. By the end of this guide, you will have the skills needed to create intelligent language applications that can handle the nuances of human communication effectively.

□ 2. Tác giả
Delip Rao is the founder of Joostware, a San Francisco-based consulting company specializing in machine learning and natural language processing research. He previously worked on NLP research and products at Twitter and Amazon (Alexa). Brian McMahan is a research engineer at Wells Fargo with a PhD in Computer Science from Rutgers University, where he built Bayesian and Deep Learning models of language and semantics.