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.
Über diesen Kurs
Kompetenzen, die Sie erwerben
University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
- 5 stars65,49 %
- 4 stars23,92 %
- 3 stars6,83 %
- 2 stars1,65 %
- 1 star2,09 %
Top-Bewertungen von TEXT RETRIEVAL AND SEARCH ENGINES
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.
This course is complemented with a software and text (not mandatory) and good explanation with diagrams...
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.
Some mistakes in subtitle. and it is better to break down the long videos into smaller sections, illustrate the concepts with more graphs,picture and animation.
Über den Spezialisierung Data-Mining
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.
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