Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.
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Great course for those trying to understand how ro analyse and process text data. It has the right amount of tools to help you understand the basics of information retrieval and search engines.
I have learned a lot of concepts through this course, but at a shallow level. It is a great introduction course to IR. It can be improved by adding more programming tasks for hands-on exercise
I will keep the last star for not using a more cutting edge programming language, e.g. python. MeTa is not really helpful in the business world and that discounts the value of this course.
I found that there were a lot of mathematical function in this course. I need to see the examples of how are those functions applied in the real programming which support the business.
关于 数据挖掘 专项课程
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp.