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所在平台: Udemy |
课程主页: https://www.udemy.com/course/understand-and-practice-ai-natural-language-processing-in-python/
课程评论：没有评论
课程名称：U & P AI - 自然语言处理 (NLP) 与 Python 课程概述：本课程面向初学者和中级学习者，不适合专家。该课程是专注于人工智能的一系列课程中的一部分，主题是理解和实践人工智能。这门课程聚焦于自然语言处理（NLP），学习关键的NLP概念和直觉训练，帮助您迅速了解NLP的各个方面。课程将以最优的方式提供信息，首先会讲解概念的定义、重要性、引发该概念思考的问题以及如何应用该概念（理解概念），接着进入实际案例或简单问题的练习（实践）。 课程内容包括： - 理解 NLP 的基本概念，例如分词、词干提取和词形还原。 - 构建 Bag of Words 模型并利用其进行文本分类。 - 使用机器学习分析给定句子的情感。 - 主题建模，并实现一个识别文档主题的系统。 - 从简单的NLP问题开始，逐步构建复杂的项目。 在课程中，您将学习如何： - 表达自然语言文本的含义。 - 建立类别预测器，以预测给定文本的类别。 - 构建基于姓名的性别识别器。 - 建立情感分析器，用于判断电影评论的情感倾向。 - 使用潜在狄利克雷分配（Latent Dirichlet Allocation）进行主题建模。 - 进行特征工程和处理语料库及WordNet。 - 处理任何NLP和机器学习模型的词汇。 学习提示： - 记录手写笔记，以提高信息保留能力。 - 在讨论区积极提问，问题越多效果越好！ - 大部分练习可能需要数天或数周才能完成。 - 自己动手编写代码，而不是仅仅看课程中提供的代码。 若您对NLP一无所知，课程将为您逐步解析！我会随时回答您的问题，帮助您在数据科学的旅程中前进。请注意，该课程将会不断更新，届时会添加新内容和新概念，敬请关注！
- UPDATED - (NEW LESSONS ARE NOT IN THE PROMO VIDEO)THIS COURSE IS FOR BEGINERS OR INTERMEDIATES, IT IS NOT FOR EXPERTSThis course is a part of a series of courses specialized in artificial intelligence: Understand and Practice AI - (NLP)This course is focusing on the NLP: Learn key NLP concepts and intuition training to get you quickly up to speed with all things NLP.I will give you the information in an optimal way, I will explain in the first video for example what is the concept, and why is it important, what is the problem that led to thinking about this concept and how can I use it (Understand the concept). In the next video, you will go to practice in a real-world project or in a simple problem using python (Practice).The first thing you will see in the video is the input and the output of the practical section so you can understand everything and you can get a clear picture!You will have all the resources at the end of this course, the full code, and some other useful links and articles.In this course, we are going to learn about natural language processing. We will discuss various concepts such as tokenization, stemming, and lemmatization to process text. We will then discuss how to build a Bag of Words model and use it to classify text. We will see how to use machine learning to analyze the sentiment of a given sentence. We will then discuss topic modeling and implement a system to identify topics in a given document. We will start with simple problems in NLP such as Tokenization Text, Stemming, Lemmatization, Chunks, Bag of Words model. and we will build some real stuff such as:Learning How to Represent the Meaning of Natural Language TextBuilding a category predictor to predict the category of a given text document. Constructing a gender identifier based on the name. Building a sentiment analyzer used to determine whether a movie review is positive or negative.Topic modeling using Latent Dirichlet AllocationFeature EngineeringDealing with corpora and WordNetDealing With your Vocabulary for any NLP and ML modelTIPS (for getting through the course):Take handwritten notes. This will drastically increase your ability to retain the information.Ask lots of questions on the discussion board. The more the better!Realize that most exercises will take you days or weeks to complete.Write code yourself, don't just sit there and look at my code.You don't know anything about NLP? let's break it down!I am always available to answer your questions and help you along your data science journey. See you in class!NOTICE that This course will be modified and I will add new content and new concepts from one time to another, so stay informed!:)
