Big Data

Literature

1. From the third week on, we largely follow the first 8 chapters of the book Understanding Machine Learning, From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David
   • you can legally download the book from a webpage of the first author
   • you can, of course, also buy this book.
   • It is a good book, so if you want to become a data scientist, buying it is a sensible choice
2. The seminal paper on association rule discovery is Fast Algorithms for Mining Association Rules, by Rakesh Agrawal and Ramakrihnan Srikant, VLDB 94
3. Hannu Toivonen's paper: Sampling Large Databases for Association Rules
4. Matteo Riondato and Eli Upfal have two papers with title "Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees"
   • the conference version in the proceedings of ECML PKDD
   • the journal version in the ACM Transactions on Knowledge Discovery from Data
5. If you need to brush up on probability theory and statistics, please watch the MIT course Introduction to Probability.
6. Two online courses that may help you understand the lectures are:
   • Shai Ben-David's lecture videos Understanding Machine Learning.
   • Yaser Abu-Mostafa's lecture videos on Learning from Data.