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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-natural-language-processing/
课程评论：没有评论
Coursera 课程《**Python 自然语言处理 (NLP)**》中文内容概述 本课程专为希望学习 Python 自然语言处理 (NLP) 概念的学生设计。 课程从 Python 基础知识的复习开始，随后介绍文本处理方法和 Pandas 库。文本处理方法在构建 NLP 项目时非常重要，Pandas 库则用于读取和分析数据集。 接着，课程将深入探讨 spaCy 库的各项功能，包括词性标注、分词和命名实体识别。spaCy 和 NLTK 是两种最受欢迎的 Python NLP 库。 在掌握了这些基础概念后，课程将进入模型性能评估部分，学习如何评估 NLP 模型的效果。 之后，我们将学习情感分析和文本分类，并通过实例进行展示。 在课程的最后部分，我们将从零开始构建一个完整的 NLP 项目，整合所学知识。 在整个课程期间及之后，学生可以通过课程的问答环节或直接消息与讲师就课程内容进行交流。 感谢您访问课程页面并阅读课程介绍。
Welcome to the landing page of Python for Natural Language Processing (NLP) course. This course is built for students who want to learn NLP concepts in Python. Course starts with the repeat of the Python Fundamentals. After it text methods and pandas library is covered in the course. Text methods will be helpful when we are going to be building Natural Language Processing projects. We will use pandas library for reading and analyzing our data sets. After it we will cover some fatures of spaCy library like part of speech tagging, tokenization and named entity recognition. spaCy with NLTK are the both most popular Python libraries for Natural Language Processing. After covering that concepts we will move into evaluation of model performances section and there we will be learning how the NLP models will be evaluated. After that task we will see Sentiment Analysis and Text Classification and we will make examples of them. At the final lectures of the course we will build a Natural Language Processing project from stratch with what we learned through the course and we will finish. At the whole course process and after it, students can reach to me about the course concepts via Q & A section of the course or direct messages on Udemy. Thanks for visiting course page and reading course description.
