Advanced Machine Learning
Core AML theory and reference
Syllabus
| Module No. | Detailed Content | Hrs (45) | CO |
|---|---|---|---|
| 1 | Generalized Linear Models and Exponential FamilyIntroduction, Exponential family, generalized Linear model, Probit regression, Multitask learning, generalized linear mixed models | 07 | CO1 |
| 2 | Directed Graphical Models Introduction, examples, inference, learning, conditional independence properties of DGM, decision diagrams | 07 | CO2 |
| 3 | Mixture Models and EM algorithmLatent variable models, Mixture models, Goals, parameter estimation of mixture models, EM algorithm, model selection for latent variable models, fitting models with missing data | 09 | CO3 |
| 4 | Markov and Hidden Markov Models Introduction, Markov models, Hidden Markov Models, Inference in HMM, learning for HMMs, generalizations of HMMs | 08 | CO4 |
| 5 | Undirected Graphical Models Introduction, Conditional independence properties of UGMs, parameterization of MRFs, examples of MRFs, learning, Conditional random fields | 07 | CO5 |
| 6 | Monte Carlo InferenceIntroduction, sampling from standard distributions, rejection sampling, importance sampling, Markov chain Monte carlo inference introduction | 07 | CO6 |
Module 1
Generalized Linear Models
Module 1 • Exponential family, Probit regression, Multitask learning, GLMM
Module 2
Directed Graphical Models
Module 2 • Introduction, examples, inference, learning, conditional independence, decision diagrams
Module 3
Mixture Models & EM algorithm
Module 3 • Latent variable models, parameter estimation, model selection, missing data
Module 4
Markov & Hidden Markov Models
Module 4 • Introduction, Markov models, HMM inference & learning, generalizations
Module 5
Undirected Graphical Models
Module 5 • MRFs conditional independence, parameterization, learning, CRFs
Module 6
Monte Carlo Inference
Module 6 • Sampling distributions, rejection & importance sampling, MCMC
Question Banks
Internal Assessment 1
Modules 1 • Modules 2
Mid-Semester Exam
Modules 1 • Modules 2 • Modules 3
End-Semester Exam
Modules 1 • Modules 2 • Modules 3 • Modules 4 • Modules 5 • Modules 6 • Extra PYQs