UE19CS303 - Machine Intelligence

Course instructors: Prof. Preet Kanwal, Prof. Preethi P

Syllabus and Class Notes

Unit	Syllabus	Vibha’s Notes
Unit 1	Search Algorithms, Classification, Decision trees, Performance metrics	MI Unit 1.pdf
Unit 2	Supervised learning with kNN, Neural Networks, SVM	MI Unit 2.pdf
Unit 3	Boosting and Stochastic Models, Bayesian learning	Bayesian Learning.pdf \

                         [Hidden Markov Models.pdf](HMM.pdf) \
                         [Ensemble Models.pdf](Ensemble%20Models.pdf) |

Unit 4 | Unsupervised Learning, Dimensionality Reduction, Genetic Algorithms | Expectation Maximization.pdf   Dimensionality Reduction.pdf   Clustering.pdf   Genetic Algorithms.pdf   Particle Swarm Optimization.pdf |
Unit 5 | Deep Learning, CN, RNN, Optimizers | Convolutional Neural Networks.pdf   LSTM and GRU.pdf   Optimizers.pdf   Regularization.pdf   Recurrent Neural Networks.pdf |