|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/applied-text-mining-and-sentiment-analysis-with-python/
课程评论：没有评论
课程名称：应用文本挖掘和情感分析与Python 课程概述： 在这个课程中，您将学习如何构建一个机器学习模型，能够理解和分类来自社交媒体（尤其是Twitter）的新闻文本。以“比特币（BTC）价格刚刚达到历史新高！”为例，这对我们而言是个好消息，但计算机是否能轻易理解这样的信息呢？本课程旨在让您掌握文本挖掘、自然语言处理（NLP）和机器学习的技术，帮助机器学习如何识别和分析情感。 课程内容： 本课程分为四个部分，每部分都提供特定领域的知识，帮助您构建自己的推特情感预测模型。 第一部分：文本挖掘简介 您将了解文本数据的基本问题及挑战，同时使用Pandas和Matplotlib等库探索推特数据集。 第二部分：文本规范化 推特数据通常很杂乱。本部分将深入清理推文，掌握文本挖掘技术及相关库（如NLTK），学习分词、词干提取和词形还原等技巧。 第三部分：文本表示 在将清理后的数据输入模型之前，您需要学习如何正确表示数据。我们将探讨在NLP中常用的方法，如词袋模型和TF-IDF，使您加深对NLTK的理解。 第四部分：机器学习建模 这是最激动人心的一步！您将整合所学知识，构建情感预测模型，并使用机器学习中最常用的库Scikit-Learn。 课程优势： 本课程与其他同类课程的不同之处在于，它不仅仅是教授文本挖掘、NLP或机器学习的一般知识。而是以情感分析为目标，深入探讨实现该目标所需的步骤和工具。完成课程后，您将准确理解情感分析模型的运作原理。 关于AIOutsider： AIOutsider成立于2020年，旨在简化人工智能的学习，让更多人接触到这一领域。课程内容设计让每个人都能轻松理解，并应用于实际问题，如情感分析。如果您想深入学习，请访问我们的网站！ 如果您想学习如何在现实生活中应用人工智能解决实际问题，赶快加入我们的课程吧！
"Bitcoin (BTC) price just reached a new ALL TIME HIGH! #cryptocurrency #bitcoin #bullish"For you and me, it seems pretty obvious that this is good news about Bitcoin, isn't it? But is it that easy for a machine to understand it?.Probably not.Well, this is exactly what this course is about: learning how to build a Machine Learning model capable of reading and classifying all this news for us!Since 2006, Twitter has been a continuously growing source of information, keeping us informed about all and nothing. It is estimated that more than 6,000 tweets are exchanged on the platform every second, making it an inexhaustible mine of information that it would be a shame not to use.Fortunately, there are different ways to process tweets in an automated way, and retrieve precise information in an instant.Interested in learning such a solution in a quick and easy way? Take a look below..._____________________________________________________What will you learn in this course?By taking this course, you will learn all the steps necessary to build your own Tweet Sentiment prediction model. That said, you will learn much more as the course is separated into 4 different parts, linked together, but providing its share of knowledge in a particular field (Text Mining, NLP and Machine Learning).SECTION 1: Introduction to Text MiningIn this first section, we will go through several general elements setting up the starting problem and the different challenges to overcome with text data. This is also the section in which we will discover our Twitter dataset, using libraries such as Pandas or Matplotlib.SECTION 2: Text NormalizationTwitter data are known to be very messy. This section will aim to clean up all our tweets in depth, using Text Mining techniques and some suitable libraries like NLTK. Tokenization, stemming or lemmatization will have no secret for you once you are done with this section.SECTION 3: Text RepresentationBefore our cleansed data can be fed to our model, we will need to learn how to represent it the right way. This section will aim to cover different methods specific to this purpose and often used in NLP (Bag-of-Words, TF-IDF, etc.). This will give us an additional opportunity to use NLTK.SECTION 4: ML ModellingFinally.the most exciting step of all! This section will be about putting together all that we have learned, in order to build our Sentiment prediction model. Above all, it will be about having an opportunity to use one of the most used libraries in Machine Learning: Scikit-Learn (SKLEARN)._____________________________________________________Why is this course different from the others I can find on the same subject?One of the key differentiators of this course is that it's not about learning Text Mining, NLP or Machine Learning in general. The objective is to pursue a very precise goal (Sentiment Analysis) and deepen all the necessary steps in order to reach this goal, by using the appropriate tools.So no, you might not yet be an unbeatable expert in Artificial Intelligence at the end of this course, sorry.but you will know exactly how, and why, your Sentiment application works so well._____________________________________________________About AIOutsiderAIOutsider was created in 2020 with the ambition of facilitating the learning of Artificial Intelligence. Too often, the field has been seen as very opaque or requiring advanced knowledge in order to be used. At AIOutsider, we want to show that this is not the case. And while there are more difficult topics to cover, there are also topics that everyone can reach, just like the one presented in this course. If you want more, don't hesitate to visit our website!_____________________________________________________So, if you are interested in learning AI and how it can be used in real life to solve practical issues like Sentiment Analysis, there is only one thing left for you to do.learn with us and join this course!
