Overview

In a world where over 7,000 languages are spoken, limiting NLP systems to English is no longer an option. Global NLP is your definitive guide to building robust, scalable, and inclusive language models that understand the diversity of human communication. Whether you're working with French, Arabic, Chinese, or low-resource languages like Swahili or Uzbek, this hands-on book equips you with practical techniques, tools, and design patterns to create multilingual and cross-lingual NLP applications. You'll learn how to handle tokenization, embeddings, machine translation, named entity recognition, and sentiment analysis across languages-using powerful libraries like spaCy, Hugging Face Transformers, and fastText. Inside, you'll discover: The unique linguistic challenges of non-English text Best practices for preprocessing and tokenizing diverse scripts and language structures Strategies for building and fine-tuning multilingual models Tools to work with low-resource languages using transfer learning and zero-shot techniques Real-world case studies in global content moderation, chatbots, and cross-language search Whether you're a data scientist, machine learning engineer, or NLP researcher, Global NLP gives you the skills to build inclusive, global-first language technologies that scale across cultures and continents.

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