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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Université de l'Illinois à Urbana-Champaign
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Meilleurs avis pour RÉCUPÉRATION DE TEXTE ET MOTEURS DE RECHERCHE
Excellent ! Well organized, presented with aptitude to detail. Definitely will recommend and take further units in this specialization.
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.
Need indetail inputs on algorithm usage and correct MeTA assignments with working scripts. That makes learning a complete curve.
A great overview of text retrieval methods. Good coverage of search engines. A longer course will cover search engine better (remember this is a 6 weeker)
À propos du Spécialisation Exploration de données
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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