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Data Science DM summary
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  • Course
  • Data Science (201400174)
  • Institution
  • Universiteit Twente (UT)
  • Book
  • An Introduction to Statistical Learning

Short summary of Data Science lectures focused on the Data Mining section and a number of additions to the book Introduction to Statistical Learning with R. To be used for the Data Science course of the Business Administration and Health Sciences study at the University of Twente. The course is als...

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Document information

  • October 26, 2023
  • 13
  • 2023/2024
  • Class notes
  • Data science professors
  • All classes

Subjects

  • university of twente
  • university of twente
  • ut
  • business administration
  • ba
  • data science
  • ds
  • health sciences
  • health sciences

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  • Business Administration
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Data Science DM
Lecture notes and some additional info from the suggested book

Suggested book: Introduction to Statistical Learning with R

, Data Mining (DM) = the process of discovering patterns in large data sets involving methods at
the intersection of machine learning, statistics, and database systems
1. Supervised techniques
2. Unsupervised techniques

Supervised techniques = learn a target function by examples, learning that involves building a
model for predicting or estimating (an output based on one or more inputs)
Unsupervised techniques = find “obvious” patterns, learning about relationships and structure
of the data

Supervised techniques
1. Decision tree
2. Neural network with weights on connections
3. (Linear) function

Decision tree = decision tree mining




Neural network with weights on connections = deep learning, model

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