[ML] Resources for Students

Một số tài nguyên về máy học sẽ được tập hơp ở đây

1. Introductory materials:

  • Encyclopedia of ML [Link]
  • Scholarpedia [Link]
  • ML Summer Schools [Link]: Most presentations are provided freely.
  • VideoLetures.net ML section [Link]
  • Various courses on “Introduction to ML“: [Stanford:  Lecture notes, video | Toronto | Cambridge]

2. Tutorials:

  • Andrew Moore’s tutorials [Link]: Good for instructors 🙂

Specialized topics:

  • Kernel methods [Link]
  • Nonparametric Bayes [Link]
  • (Partially Observed) Markov Decision Process – (PO)MDP [Link 1 | Link 2]
  • Transfer Learning [Link]

4. Softwares:

  • ML Open source softwares: [Link]
  • Weka [Link]
  • Rapid Miner [Link]
  • Elefant [Link]
  • Googles prediction API [Link]

5. Datasets:

  • DMOz’s ML Dataset directory: [Link]
  • Google’s ML Dataset ranking: [Link]
  • UCI Machine Learning Repository: [Link]

6. Misc:

  • An interesting ML Survey by Yee Whye Teh (April 2011) [Link]

7. Conferences

These following conferences are attended by the most of ML people (taken from Yee Whye Teh’s survey)

8. Journals:

IEEE Trans. on Pattern Analysis and Machine Intelligence,
Jnl. of Machine Learning Research,
Neural Computation
Data Mining and Knowledge Discovery,

Machine Learning,
IEEE Trans. on Neural Networks,
Neural Networks,
Pattern Recognition,

ACM Trans. on Knowledge Discovery From Data,
Intelligent Data Analysis,


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