Recommender systems - Study guides, Class notes & Summaries

This summary consists of all the information and theory given in the lectures of the Data Mining course in 2020/2021. This theory forms an important basis for the Data Mining related implementations in Python and/or other programming software. Moreover, this summary includes some additional examples as well as a symbols and notation 'cheatsheet' to help you pass your Data Mining exam!

Summary of the Machine Learning course, taught at Maastricht University. Contains at least the following topics: ai regression (logistic and linear) bayesian networks graphs classification tasks/models clustering decision trees confidence intervals neural nets recommender systems support vector machine instance based learning (nearest neighbour) reinforcement learning

Programing ebook

The two chapters you need to learn for the CI exam.

Clear summary of all lectures in the course Marketing Analytics for Big Data. Including explained examples.

Summary for the course 0HM270 SuperCrunchers (2019-2020), formally part of the Human-Technology Interaction master program at the University of Technology Eindhoven. The summary covers all the lecture material, including all material covered in the slides (including figures) as well as all of the required readings (i.e. all separate articles provided per topic).

Summary of the theory for Advances in Data Mining for the Computer Science master at Leiden University. Covers tokenization, Recommender Systems (Naive methods, Collaborative filtering, Matrix Factorization), RBM, Similarity Search (shingling, minhashing, LSH) and Pagerank (Markov process, RageRank algorithm) It is missing the part about Support Vector machines, the last bit of minhasing and the part of the DGIM algorithm for data streams and. Parts missing are labeled with a colored marking.

I passed this course with a 7,5. Concise summary including all papers, case studies, lectures and sample exam questions: - Frey & Steiner (2012): Pay as you go - Caves (2003): Contracts between art and commerce - Hirsch: Fads and fashions, the cultural industries (revisited) - Wijnberg & Gemser (2000): Adding value to innovation: impressionism and the transformation of the selection system in visual arts. - Peltoniemi (2014): Cultural industries: product-market characteristics, management chal...