Python自然语言处理指南，第二版

English | ISBN: 1803245743 | 2024 | EPUB | 312 pages | 6 MB

Saurabh Chakravarty, Zhenya Antić, "Python Natural Language Processing Cookbook: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries, 2nd Edition"

Harness the power of Natural Language Processing to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess.

You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs.

This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust and transparency in your NLP models.

By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.

中文| ISBN:1803245743|2024|EPUB | 312页| 6 MB Saurabh Chakravarty，Zhenya Antić，“Python自然语言处理食谱：使用Python和LLM库构建强大NLP解决方案的60多种食谱，第2版” 利用自然语言处理的力量，通过两位经验丰富的NLP专家撰写的基于配方的路线图来克服现实世界的文本分析挑战，他们凭借NLP技术在改变各个行业方面拥有丰富的经验。 您将能够充分利用NLP的最新进展，包括大型语言模型（LLM），并通过Hugging Face转换器利用它们的功能。通过一系列实践食谱，您将掌握提取实体和可视化文本数据等基本技术。作者将熟练地指导您使用spaCy、Gensim和NLTK等流行库构建情感分析、主题建模和问答的管道。您还将学习如何实现RAG管道，以使用LLM从文本语料库中提取精确的答案。 第二版通过GPT-4、自然语言理解（NLU）和可解释人工智能（XAI）等前沿LLM的新章节扩展了您的技能，从而在NLP模型中培养了信任和透明度。 在本书结束时，您将掌握应用高级文本处理技术、使用预训练的变换器模型、构建自定义NLP管道以从文本数据中提取有价值的见解以推动明智决策的技能。

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