Data Mining

 

 


 

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E.g., 2017-09-18
E.g., 2017-09-18
E.g., 2017-09-18
Sep 25th 2017

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery.

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Sep 25th 2017

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.

Average: 7.5 (4 votes)
Sep 25th 2017

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery.

Average: 7.8 (5 votes)

Sep 25th 2017

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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Sep 18th 2017

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.

Average: 7.2 (5 votes)
Sep 18th 2017

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.

Average: 6.5 (2 votes)

Sep 17th 2017

El curso de BIG DATA MARKETING pretende brindar a los participantes una mirada del papel que juegan las TICs en las acciones de mercadeo a partir de la recolección y análisis de los datos de clientes y consumidores en amplios contextos de interrelación que tienen las Organizaciones con la sociedad. Así mismo motive a utilizar herramientas de Big Data para realizar análisis pertinentes. consolidando información que agregue valor a la organización.

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Sep 4th 2017

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis.

Average: 7.5 (6 votes)
Aug 21st 2017

A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning. The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data. The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program, is for you to learn how to build these components and connect them using modern tools and techniques.

Average: 3 (1 vote)
Jun 19th 2017

Learn how and when to use key methods for educational data mining and learning analytics on large-scale educational data.

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May 8th 2017

Learn more about practical data mining, including how to deal with large data sets. Use advanced techniques to mine your own data! This course introduces advanced data mining skills, following on from Data Mining with Weka.

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Mar 6th 2017

Discover practical data mining and learn to mine your own data using the popular Weka workbench. Today’s world generates more data than ever before! Being able to turn it into useful information is a key skill. This course introduces you to practical data mining using the Weka workbench.

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