FenixEdu™

Mohammed J. Zaki, Wagner Meira, Jr. Data Mining and Analysis: Fundamental Concepts and Algorithms. 2014 Cambridge University Press

Jiawei Han, Micheline Kamber, and Jian Pei. Data Mining: Concepts and Techniques, 3rd edition, Morgan Kaufmann, 2011

Texts about Ethical Concerns in Data Science

GDPR.
Doing good data science, by DJ Patil, Hilary Mason and Mike Loukides. O'Riley. July 10, 2018.
The ethical side of data science and AI, by Shreyas S. Medium. Oct 21, 2018
Physiognomy?s New Clothes, by Blaise Aguera y Arcas. Medium. May 7, 2017
How big data is unfair - Understanding unintended sources of unfairness in data driven decision making, by Moritz Hardt. Medium. Sep 26, 2014

Slides

T1a - Introduction and organization
T1b - Data Science (Han 1, Zaki 1)
T2 - Data Exploration (Han 2, Zaki 2 & 3)
T3 - Data Visualization (Few)
T4 - Classification: Analogizers (Han 9.5 & 9.3, Zaki 18.3 & 21.1)
T5 - Classification: Bayesians (Han 8.3 & 8.5, Zaki 18)
T6 - Overfitting, Training strategies, Data Balancing, ROC charts (Han 12, Zaki 22)
T7,8 - Classification: Decision Trees (Han 8.2, Zaki 19, Wu&Kumar 10)
T9 - Classification: Ensemble Methods (Han 8.6)
T10 - Classification: connectionists (Han 9.2)
T11 - Classification: genetic algorithms
T12 - Pattern Mining (Han 6 & 7, Zaki 8 & 9 & 10 & 12)
T13,14 - Clustering (Han 10 & 11.1, Zaki 13-17)
T15 - Data Reduction: Feature Selection (Han 3.4 & 3.5, Zaki 6 & 7)
T16 - Data Reduction: Principal Component Analysis (check T15 references)
T17 - Regression (not covered in bibliography, Gelman&Hill part 1A)
T18 - Biclustering (not covered in bibliography, Madeira&Oliveira, Henriques&Madeira)
T19 - Outlier Analysis (not covered in bibliography, Aggarwal)
T20 - Network Data Analysis (Aggarwal2011-1&2, Wu&Kumar 6)
T21 - Temporal Data Mining (not covered in bibliography, Esling&Agon, Mörchen)
T22 - Time Series Description and Forecasting (not covered in bibliography, Bisgaard&Kulahci)
T23 - Complex Data Mining (not covered in bibliography, Atluri&Karpatne&Kumar and Dzeroski)
T24 - Notes on Big Data Analysis (not covered in bibliography, Zaki and Aggarwal)
T25 - Privacy an Ethical Concerns
T26 - Closing remarks (no slides)

Exercises Book: Part I
Exercises Book: Part II
- PAA, SAX, SDFT and Wavelet transformations will not be covered in the final exam

T13,14 (clustering): slides 5,6,12,14,15,18,20,22-40,49-71,83-98,108-112,115,120,121
T15 (data reduction): slides 4-32,36-43
T16 (PCA): slides 5-27,33,34,45,46
T17 (regression): slides 3-43,49-52
T18 (biclustering): slides 3-35,49,53,54
T19 (outlier analysis): 3-11,14,19,21,23,26,27
T21 (temporal data mining): 4-20,24-30,34-45,48
T22 (time series forecasting): 4-6,10-15,18-37,40-51,53,55-63,66-73
T23 (complex data mining): 4,12-14,17,20,21,24-29,32,34-36,39,41,43,44,48,50-54,60,61
T24 (big data analysis): 3-13,15,18,21,22,31,33
Remaining lectures: full PPT as study reference
Final exam will not ask for definitions or a memory-based listing of slide contents