Erinevus lehekülje "Data Mining and network analysis IDN0110" redaktsioonide vahel

Allikas: Kursused
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85. rida: 85. rida:
 
== Lecture 12  Social Network Analysis ==
 
== Lecture 12  Social Network Analysis ==
 
[[Media:Lecture_12_DM2018_Social_Network_analysis.pdf ‎|Slides]]
 
[[Media:Lecture_12_DM2018_Social_Network_analysis.pdf ‎|Slides]]
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== Lecture 13  Privacy preserving data mining ==
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[[Media:Lecture_13_DM2018_Privacy_preserving_data_mining.pdf ‎|Slides]]
  
  

Redaktsioon: 15. detsember 2018, kell 18:06

Fall 2018/2019

IDN0110 / ITI8730: Data Mining and network analysis Taught by: Sven Nõmm EAP: 6.0

Examination (final project defense) and Consultations times

4.01 16:00-17:00 Consultation, make up for Closed book test 2. (If you wish to defend your project this date please contact lecturer in advance.)

10.01 16:00- 17:45 Examination (final project defense)

17.01 16:00 – 17:00 Consultation

23.01 16:00- 17:45 Examination (final project defense)



 Lectures: Wednesdays      14:00-15:30  ICT-A1
 Labs:     Thursdays       16:00-17:30  ICT-401


Consultation: by appointment only Please do not hesitate to ask for appointment!!! For communication please use the following e-mail: sven.nomm@ttu.ee

Overview

The course aims to provide knowledge of theory behind different methods of data mining and develop practical skills in applying those methods on practice. Is is spanned around four "super problems" of data mining:

  • Clustering
  • Classification
  • Association pattern mining
  • Outlier analysis

Main topics of the course:

  • Data types and Data Preparation
  • Similarity and Distances, Association Pattern Mining,
  • Cluster Analysis, Classification, Outlier analysis
  • Data streams, Text Data, Time Series, Discrete Sequences,
  • Spatial Data, Graph Data, Web Data, Social Network Analysis

Evaluation

  • 2x mandatory closed book tests. Each test gives 10% of the final grade.
  • 3x mandatory home assignments (Computational assignment +short write up.) Each assignment gives 10% of the final grade.
  • final exam (gives 50 % of the final grade): Written report on assigned topic + discussion with lecturer.

Exam prerequisites: both closed book tests are accepted (graded as 51 or higher), all 3 home assignments are accepted (graded as 51 or higher).

Home assignments, code examples, data files and useful links will be distributed by means of ained.ttu.ee environment. Course enrollment process will be conducted during the first lecture.

Lectures

Lecture 1 Introduction and data preparation

Slides

Lecture 2 Similarity and distance

Slides

Lecture 3 Cluster analysis

Slides

Lecture 4 Classification

Slides

Lecture 5 Anomaly and Outlier Analysis

Slides

Practice 5 Implementation of EM - Algorithm

Slides

Lecture 6 Association Pattern Mining

Slides

Lecture 7 Similarity and Distance 2

Slides

Lecture 8 Text Data Mining

Slides

Lecture 9 Time Series Mining

Slides

Lecture 10 Data Streams Mining

Slides

Lecture 11 Graph Data Mining

Slides

Lecture 12 Social Network Analysis

Slides

Lecture 13 Privacy preserving data mining

Slides


Make up for Closed book test 1 will take place on 13.12.2018, usual practice time

Closed book test 2 will take place on 19.12.2018, usual lecture time

Make up for Closed book test 2 will take place on 04.01.2019, during the Consultation in ICT-401 16:00