[TZI]  [Computer Science Department]  [University of Bremen] 

Vorlesungsfolien / slides

Übungen / exercises

Praktika / practica

Quelltext / code

Unterlagen / scripts

Prüfung/Exam

Charles Elkan's Video on Matrix Factorization and Link Prediction

Charles Elkan's Videos on Log-Linear Models and Conditional Random Fields

PCA (Blog)

Stanford Machine Learning (Lecture Notes from Ng's Course)

Wissensbasierte Korrelation und Anomalie-Erkennung in der Internetsicherheit (Tool Video)

WEKA Toolkit

Deep Learning Toolkit


Maschinelles Lernen /
Machine Learning

Dozent/Lecturer

Stefan Edelkamp
         Am Fallturm 1, Raum 2.62 
         D-28357 Universität Bremen

Termine/Dates

Kompakt 27.02.-10.03.2017 je 08:30-12:00 / 27.02.-10.03.2017 je 14:00-16:00

Thema/Topic

Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that learn to recognize human faces, recommend music and movies, and drive autonomous robots).
  • Decision Trees, Naive Bayes, Bayes' Nets
  • Linear Regression, Markov Chains, HMMs and CRF
  • Classification 1: Neuronal Nets, Backprop and Co.
  • Classification 2: Support/Bit Vector Machines and Co.
  • Clustering: k-means and Co.
  • (Approx.) Nearest Neighbor, Full Delaunay Hierarchies, kD Trees and Co.
  • Singular Value Decomp. Principle Component Analysis and Co
  • Rule Learning: Words, Macros, Association Rules and Co.
  • Reinforcement Learning: Value Iteration and Co.
  • Recommender Systems: Collaborative Filtering and Co.
  • Regular Languages: Automata Learning, (I)ID and Co.
  • Evolutionary Learning: GAs and Co.
  • Monte-Carlo (Tree) Search: Bandits, UCT, NMCS, NRPA, and Co.
  • Deep Learning: CNN, Deep Mind and Co.

Literatur/e

  • Christopher M. Bishop: Pattern Recognition and Machine Learning Information Science and Statistics.
  • Tom Mitchell: Machine Learning, McGraw Hill.
  • Pat Langley: Elements of Machine Learning, Morgan Kaufmann.
  • Stefan Edelkamp: Heuristic Search, Morgan Kaufmann.
  • Richard Sutton, Andrew Barto: Reinforcement Learning, MIT.
  • Recent Publications in AI conferences (e.g., AAAI, IJCAI, ECML, ICML).

Machine Learning

Stefan Edelkamp (edelkamp@tzi.de)