Historical snapshot — AY2022/2023 Semester 2 · View current offering →
ModsIE4497AY2022/2023 Semester 2
Pattern Recognition Deep Learning
AY2022/2023 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, ARED, BCE, BCG, BEEC, BIE, BMS, BS, BSB, BSPY, BUS, CBE, CBEC, CE, CEE, CEEC, CHEM, CHIN, CNEL, CNLM, 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(NULL), ME(RMS), MEEC(DES), MEEC(NULL), MEEC(RMS), MS(ITG), MS(NULL), MS-2ndMaj/Spec(MSB), MTEC, 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), SCED, SOC, SSM |
| Not Available As BDE/UE To Programme | EEE, EEEC, IEEC, IEM, REP(EEE) |
| Exam |
Available Indexes
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| 1800 |