Historical snapshot — AY2025/2026 Semester 2 · View current offering →
ModsIE4497AY2025/2026 Semester 2
Pattern Recognition Deep Learning
AY2025/2026 Semester 2
This course introduces the fundamental concepts and methods in pattern recognition and machine learning. Topics covered include Introduction, Bayesian Inference, Mixture Models and EM Algorithm, Markov Models and Hidden Markov Models, Sampling, Markov chain Monte Carlo (MCMC), Neural Networks, Deep Learning (CNN, RNN), Training Deep Networks, Deep Network Architectures, Applications, Generative Models and Self-Supervised Learning.
| AUs | 3.0 AUs |
| Categories | CoreBDE |
| Not Available To Programme | ACBS, ACC, ADM, AISC, ARED, BACF, BASA, BCE, BCG, BEEC, BIE, BMS, BS, BSB, BSPY, BUS, CBE, CBEC, CE, CEE, CEEC, CHEM, CHIN, CMED, CNEL, CNLM, COMP, CS, CSC, CSEC, CVEC, DSAI, ECMA, ECON, ECPP, ECPS, EESS, ELAH, ELH, ELHS, ELPL, ENE, ENEC, ENG, ESPP, HIST, HSCN, HSLM, LMEL, LMPL, LMS, MACS, MAEC, MAEO, MAT, MATH, ME(DES), ME(IMS), ME(NULL), ME(RMS), MEEC(DES), MEEC(IMS), MEEC(NULL), MEEC(RMS), MS(ITG), MS(NULL), MS-2ndMaj/Spec(MSB), MTEC, PESC, PHIL, PHY, PLCN, PLHS, PPGA, PSLM, PSMA, PSY, REP(ASEN), REP(BIE), REP(CBE), REP(CE), REP(CSC), REP(CVEN), REP(ENE), REP(MAT), REP(ME), ROBO, SCED, SOC, SPPE, SSM |
| Exam |
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 930 | COMMON LEC (EELE) 0930-1220 Tue LT27 | ||||
| 1000 | |||||
| 1030 | |||||
| 1100 | |||||
| 1130 | |||||
| 1200 |