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所在平台: Udemy |
课程主页: https://www.udemy.com/course/a-comprehensive-guide-to-nltk-in-python-volume-1/
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课程名称：《NLTK在Python中的全面指南：第一卷》 课程概述： 欢迎参加《NLTK在Python中的全面指南：第一卷》。这是一个系列课程中的第一个，专注于自然语言处理工具包（NLTK）。NLTK是一个全面的Python库，适用于自然语言处理和文本分析。本课程并不是关于构建模型的，而是专注于自然语言处理的一个特定部分——标记化（tokenization）。标记化是将文本分解为句子和单词的过程，是后续课程中所需技术的基础。 本课程将覆盖文本标记化的基础知识，并介绍WordNet，后者是为自然语言处理系统提供程序访问的字典。我们将以广泛的视角来看待自然语言处理，涉及从简单的单词频率计数到复杂的人类表达理解的各种内容。自然语言处理（NLP）的技术在日常生活中越来越普及，例如手机和手持设备的预测文本和手写识别功能，网络搜索引擎从非结构化文本中提取信息，机器翻译让我们能够将中文文本转换为西班牙语阅读，以及文本分析帮助我们检测推文和博客中的情感。 本课程的所有教程都将在Jupyter Notebook中创建，Jupyter是一个允许您交互性编写和注释Python代码的Web应用程序，非常适合实验、研究和分享工作进展。 作为对课程的兴趣感谢，我们鼓励您查看免费提供的预览课，了解Python的安装和基本使用。 感谢您对《NLTK在Python中的全面指南：第一卷》的关注！
Recent Course Review: "Great course! The things that Mike taught are practical and can be applied in the real world immediately." - Ricky Valencia Welcome to A Comprehensive Guide to NLTK in Python: Volume 1 This is the very FIRST course in a series of courses that will focus on NLTK. Natural Language ToolKit (NLTK) is a comprehensive Python library for natural language processing and text analytics. Note: This isn't a modeling building course. This course is laser focused on a very specific part of natural language processing called tokenization. This is the first part in a series of courses crafted to help you master NLP. This course will cover the basics of tokenizing text and using WordNet Tokenization is a method of breaking up a piece of text into many pieces, such as sentences and words, and is an essential first step for recipes in the later courses. WordNet is a dictionary designed for programmatic access by natural language processing systems. NLTK was originally created in 2001 as part of a computational linguistics course in the Department of Computer and Information Science at the University of Pennsylvania We will take Natural Language Processing - or NLP for short - in a wide sense to cover any kind of computer manipulation of natural language. At one extreme, it could be as simple as counting word frequencies to compare different writing styles. At the other extreme, NLP involves "understanding" complete human utterances, at least to the extent of being able to give useful responses to them. Technologies based on NLP are becoming increasingly widespread. For example, phones and handheld computers support predictive text and handwriting recognition; web search engines give access to information locked up in unstructured text; machine translation allows us to retrieve texts written in Chinese and read them in Spanish; text analysis enables us to detect sentiment in tweets and blogs. A Jupyter notebook is a web app that allows you to write and annotate Python code interactively. It's a great way to experiment, do research, and share what you are working on. In this course all of the tutorials will be created using jupyter notebooks. In the preview lessons we install Python. Check them out. They are completely free. By providing more natural human-machine interfaces, and more sophisticated access to stored information, language processing has come to play a central role in the multilingual information society. Thanks for your interest in A Comprehensive Guide to NLTK in Python: Volume 1
