Python入门:探索自然语言处理的实践与算法

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《Python自然语言处理(影印版)》是一本由Steven Bird、Ewan Klein和Edward Loper合著的实用指南,专为希望入门自然语言处理(Natural Language Processing, NLP)领域的读者设计。本书强调了使用Python语言进行NLP实践的重要性,旨在让读者掌握如何处理大量的非结构化文本数据,如文本分类、情感分析、自动摘要和机器翻译等技术。 书中内容覆盖了广泛的NLP基础知识,包括语言数据结构的使用,如词袋模型、n-gram、TF-IDF等,这些数据结构是理解和分析书面沟通的关键工具。作者会指导读者如何通过编写Python代码来构建和应用这些模型,例如使用正则表达式进行文本预处理,或者利用nltk(Natural Language Toolkit)这样的Python库进行更复杂的语法分析和词法分析。 此外,书中还深入介绍了主要的NLP算法,如朴素贝叶斯分类器、支持向量机、最大熵模型以及深度学习中的循环神经网络(RNN)和Transformer等,这些都是实现文本预测和理解的重要手段。读者将学习如何训练模型以识别垃圾邮件、新闻主题、情感极性,甚至进行文本自动生成和翻译。 《Python自然语言处理(影印版)》不仅仅是一本技术手册,它还注重理论与实践相结合,鼓励读者通过实际项目来巩固所学知识。书中提供的综合语言数据集,如新闻文本、电影评论、社交媒体帖子等,使得读者有机会在真实数据上验证和优化自己的算法。 最后,本书的出版信息显示,它于2009年首次发行,不断更新以适应快速发展的NLP技术。O'Reilly Media作为出版社,提供了丰富的在线资源和教育服务,确保读者能够获取最新和最全面的NLP教育资源。 《Python自然语言处理(影印版)》是一本适合初学者和专业人士的实用教程,它详细介绍了如何使用Python语言探索并应用自然语言处理技术,是任何对NLP感兴趣的开发者或研究者必备的参考资料。通过阅读这本书,读者将获得坚实的基础,为进一步研究和开发基于自然语言的智能应用打下坚实的基础。
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Python Natural Language Processing by Jalaj Thanaki English | 31 July 2017 | ISBN: 1787121429 | ASIN: B072B8YWCJ | 486 Pages | AZW3 | 11.02 MB Key Features Implement Machine Learning and Deep Learning techniques for efficient natural language processing Get started with NLTK and implement NLP in your applications with ease Understand and interpret human languages with the power of text analysis via Python Book Description This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world. What you will learn Focus on Python programming paradigms, which are used to develop NLP applications Understand corpus analysis and different types of data attribute. Learn NLP using Python libraries such as NLTK, Polyglot,