[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:

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

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

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

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