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  • Welcome to COMP90051
  • Revision Progress
  • Basic Concepts
  • Resources
  • Final Review Notes
  • Short Answer Questions
    • Short Answers
  • Relationship
  • week1
    • Lecture 1.
    • Lecture 2.
    • Additional notes
    • worksheet2note
  • week2
    • Lecture 3.
    • Lecture 4.
    • Additional notes
    • worksheet3note
  • week3
    • Lecture 5. Regularization
    • Lecture 6. PAC Learning Theory
    • Additional notes
    • worksheet4note
  • week4
    • Lecture 7. VC Theory
    • Lecture 8. Support Vector Machines
    • Additional notes
    • worksheet5note
  • week5
    • Lecture 9. Kernel Methods
    • Lecture 10. The Perceptron
    • Additional notes
    • worksheet6note
  • week6
    • Lecture 11. Neural Network Fundamentals
    • Lecture 12.
    • Additional notes
  • week7
    • Lecture 13. Convolutional Neural Networks
    • Lecture 14. RNN
    • Additional Resource
  • week8
    • Lecture 16 Graph Convolution Networks (Deep Learning After You Drop The Camera)
    • Lecture 16. Learning with expert advice
  • week9
    • Stochastic Multi-Armed Bandits (MABs)
    • Bayesian regression
    • Workshop 10: Multi-armed bandits notes
  • week10
    • Bayesian classification
    • PGM Representation
    • Additional Notes - More on Bayesian
  • week11
    • U-PGM
    • SVM assignment
    • Lecture 22. Inference on PGMs
    • ASM2 feedback
  • week12
    • Lecture 22. Inference on PGMs Cont. & Lecture 23. Gaussian Mixture Models
    • Lecture 24. Subject Review and Exam Info
  • Review Notes
    • Review 0
    • Review 1
    • Review 2
    • Review 3
    • Review 4
    • Review 5
  • Repository
  • Open issue
  • .md

week8

week8#

This notes is completed with assistance of ChatGPT

View Lecture 15. Graph Convolution Networks

View Lecture 16. Learning with expert advice

View workshop9-slides

View workshop9

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Additional Resource

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Lecture 16 Graph Convolution Networks (Deep Learning After You Drop The Camera)

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