Data Mining

Mathematical methods for large scale data analytics and prediciton

Syllabus

  1. Introduction to Data Mining
  2. Data Processing
  3. Linear Regression Models
  4. Linear Classification Models
  5. Logistic Regression
  6. Perceptron
  7. Multi-layer Perceptron
  8. Support Vector Machines
  9. Model Selection
  10. Unsupervised Learning
  11. Cluster Analysis
  12. Combinatorial Algorithms
  13. Principal Component Analysis
  14. Self-organizing Maps
  15. High Dimensional Problems

Final Project

  1. Guidelines

Final Projects

  1. FIFA World Cup
  2. Complete Cryptocurrency Market History
  3. Sign Language Interpretation
  4. Human Activity Recognition
  5. 10 Monkey Species
  6. Urban Sound Classification
  7. Avocado Prices
  8. Credit Card Fraud Detection
  9. Daily Happiness and Employee turnover
  10. My Anime List
  11. Pokemon Images
  12. Extended MNIST
  13. Schizophrenia
  14. The Simpsons Characters Data
  15. RSNA Bone Age
  16. Netflix Prize Data

Reference

  1. Data Mining, Concepts and Techniques, Jiawei Han, 2012
  2. The Elements of Statistical Learning, Trevor Hastie, Springer, 2009

Exercise Sheets

  1. Exercise Sheet 1
  2. Exercise Sheet 2
  3. Mini Project 1
  4. Exercise Sheet 3

Datasets

  1. Wine Dataset
  2. Iris Dataset

Julia Notebooks

  1. Data Cleaning
  2. Linear Regression - Wine Example

Matlab Lab

  1. Clustering Lab
  2. PCA Lab
  3. SOM Lab
  4. Hierarchical Clustering and NMF
  5. hc.m

Material

  1. Python Online Material
  2. Tensorflow Documentation
  3. Julia Language
  4. Julia Tutorials