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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-python-natural-language-toolkit-nltk-for-text-mining/
课程评论：没有评论
**课程名称：** 使用 Python 和 NLTK 进行自然语言处理 **课程概述：** 本课程深入探讨文本挖掘和自然语言处理 (NLP)，重点介绍使用 Python 的自然语言工具包 (NLTK) 进行 NLP。您将学习关键的文本预处理技术，为任何 NLP 应用做好数据准备。课程内容涵盖文本清理、词干提取、词形还原、词性标注和停用词移除，并深入讲解 NLTK 的组件和功能，而非快速介绍。 **课程内容：** * **第一部分：** 介绍 NLP 的定义、应用以及如何安装和使用 NLTK 及其组件。 * **第二部分：** 深入学习 NLTK 的核心功能、方法和技术，并探索不同的文本数据预处理算法。 * **第三部分：** 通过构建三个实际的 NLP 应用来巩固所学知识： * **主题建模应用：** 识别大型文本中的主要话题。 * **文本摘要应用：** 训练计算机自动总结长文本并提取要点。 * **情感分析应用：** 构建一个情感分析系统，以 Twitter 数据为例进行演示。 **课程亮点：** 课程最后还将对比 NLTK 和另一个流行的 NLP 库 SpaCy。这是一门实践性强、内容丰富的课程，旨在帮助您掌握 NLP 的核心技能。
Text mining and Natural Language Processing (NLP) are among the most active research areas. Pre-processing your text data before feeding it to an algorithm is a crucial part of NLP. In this course, you will learn NLP using natural language toolkit (NLTK), which is part of the Python. You will learn pre-processing of data to make it ready for any NLP application.We go through text cleaning, stemming, lemmatization, part of speech tagging, and stop words removal. The difference between this course and others is that this course dives deep into the NLTK, instead of teaching everything in a fast pace.This course has 3 sections. In the first section, you will learn the definition of NLP and its applications. Additionally, you will learn how to install NLTK and learn about its components.In the second section, you will learn the core functions of NLTK and its methods and techniques. We examine different available algorithms for pre-processing text data.In the last section, we will build 3 NLP applications using the methods we learnt in the previous section.Specifically, we will go through developing a topic modeling application to identify topics in a large text. We will identify main topics discussed in a large corpus.Then, we will build a text summarization application. We will teach the computer to summarize the large text and to summarize the important points.The last application is about sentiment analysis. Sentiment analysis in Python is a very popular application that can be used on variety of text data. One of its applications is Twitter sentiment analysis. Since tweets are short piece of text, they are ideal for sentiment analysis. We will go through building a sentiment analysis system in the last example.Finally, we compare NLTK with SpaCy, which is another popular NLP library in Python. It's going to be a very exciting course. Let's start learning.
