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Welcome to COMP90051
Revision Progress
Basic Concepts
Resources
Final Review Notes
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
.pdf
Lecture 7. VC Theory
Lecture 7. VC Theory
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see review3: vc-dimension
