Udemy

More Data Mining with R

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  • 2,610 Students
  • Updated 8/2020
3.7
(111 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
10 Hour(s) 34 Minute(s)
Language
English
Taught by
Geoffrey Hubona, Ph.D.
Rating
3.7
(111 Ratings)

Course Overview

More Data Mining with R

How to perform market basket analysis, analyze social networks, mine Twitter data, text, and time series data.

More Data Mining with R presents a comprehensive overview of a myriad of contemporary data mining techniques. More Data Mining with R is the logical follow-on course to the preceding Udemy course Data Mining with R: Go from Beginner to Advanced although it is not necessary to take these courses in sequential order. Both courses examine and explain a number of data mining methods and techniques, using concrete data mining modeling examples, extended case studies, and real data sets. Whereas the preceding Data Mining with R: Go from Beginner to Advanced course focuses on: (1) linear, logistic and local polynomial regression; (2) decision, classification and regression trees (CART); (3) random forests; and (4) cluster analysis techniques, this course, More Data Mining with R presents detailed instruction and plentiful "hands-on" examples about: (1) association analysis (or market basket analysis) and creating, mining and interpreting association rules using several case examples; (2) network analysis, including the versatile iGraph visualization capabilities, as well as social network data mining analysis cases (marriage and power; friendship links); (3) text mining using Twitter data and word clouds; (4) text and string manipulation, including the use of 'regular expressions'; (5) time series data mining and analysis, including an extended case study forecasting house price indices in Canberra, Australia.

Course Content

  • 9 section(s)
  • 67 lecture(s)
  • Section 1 Introduction to R and to Data Mining
  • Section 2 Association Analysis (part 1)
  • Section 3 Association Analysis: Online Radio and Predicting Income
  • Section 4 Social Network Analysis: iGraph Visualizations
  • Section 5 Social Network Analysis (part 2)
  • Section 6 Text Mining Twitter Data
  • Section 7 Text (String) Manipulation
  • Section 8 Time Series Data Mining
  • Section 9 Case Study: Forecasting House Price Indices in Canberra, Australia

What You’ll Learn

  • Understand the conceptual foundations of association analysis and perform market basket analyses., Be able to create visualizations of social (and other) networks using the iGraph package., Understand how to examine and mine social network data to understand all of the implicit relationships., Mine text data to create word association visualizations, term documents with word frequency counts and associations, and create word clouds., Learn how to process text and string data, including the use of 'regular expressions'., Extract prototypical information about cycles from time series data.


Reviews

  • A
    Antonina Milekhina
    1.0

    I'm disappointed that lecturer is not able to explain some things and is referring to "I've tried but could not understand". I don't think this is worth mentioning if you really tried and have not understood.

  • J
    Juan Carlos Villarreal
    5.0

    This course is very informative and well explained. Excellent video.

  • M
    Maria Caro
    3.0

    The sound quality could be better. The lectures are a recording of an live streaming class. I wouldn't have bought the course if I have realized it.

  • S
    Sven Kunsing
    2.5

    Seems that the lecturer could have prepared a little bit better for making the videos, not to get puzzled and lost in its own code.

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