* class lectures * {{:lecture_1.ppt|Lecture 1}} * {{:lecture_2.ppt|Lecture 2}} * {{:lecture_3.ppt|Lecture 3}} * {{:lecture_4.ppt|Lecture 4}} * {{:lecture_5.ppt|Lecture 5}} * {{:lecture_6.ppt|Lecture 6}} * {{:lecture_7.ppt|Lecture 7}} * {{:lecture_8.ppt|Lecture 8}} * {{:lecture_9.ppt|Lecture 9}} * {{:lecture_10b.ppt|Lecture 10}} * {{:lecture_11.ppt|Lecture 11}} * {{:lecture_12.ppt|Lecture 12}} * {{:vector_space_model-updated.ppt|Lecture 13 razieh}} * {{:lecture_13_ir_and_vsm_.ppt|Lecture 13 alternative}} * {{:lecture_14_text_classification.ppt|Lecture 14 elnaz}} * {{:lecture_14_text_classification_.ppt|Lecture 14 alternative incomplete}} * {{:lecture_14_-_cohen.ppt|Lecture 14 alternative 2}} * {{:lecture_15_6390e_mee_parser_clustering_cng.ppt|Lecture 15 ameeta}} * {{:lecture_16_haluk-presentation.pdf|Lecture 16 haluk - probabilistic modelling and joint distribution model}} * {{:lecture_17_fullyindependentandnaivebayesmodels-ny.pdf|Lecture 17 nikolay}} * {{:n-gram_presentation.ppt|Lecture 18 razieh}} * {{:lecture_18_ngram_models.pps.ppt|Lecture 18 bahareh}} * {{:hmm.ppt|Lecture 19 leah}} * {{:lecture_19_cl_-_hidden_markov_models.pdf|Lecture 19 rados}} * {{:hmm.ppt|Lecture 19 leah}} * {{:bayesian_network.pdf|Lecture 20 Bart}} * {{:lecture_20_bayesian-networks.ppt|Lecture 20 nariman}} * {{:lecture_21_probabilisticparsing.ppt|Lecture 21 dmitri}} * miscellaneous lectures * {{:fsa-re-2009.pdf|FSA}} * {{:just-in-time.ppt|just in time subgrammar extraction}} * {{:modularhpsg.ppt|modular hpsg}} * {{:kn-talk.ppt|machine translation}} * {{:dtree18.pdf|decision trees}} * {{:gmm14.pdf|clustering with gaussian mixtures}} * {{:cpe480lecture_04.ppt|syntax}} * {{:cpe480lecture_05-1.ppt|parsing}} * {{:cpe480lecture_06.ppt|semantics}} * {{:tagging_slides.pdf|tagging}} * statistical machine translation - esslli * {{:esslli-slides-day1.pdf|esslli 1}} * {{:esslli-slides-day2.pdf|esslli 2}} * {{:esslli-slides-day3.pdf|esslli 3}} * {{:esslli-slides-day4.pdf|esslli 4}} * {{:esslli-slides-day5.pdf|esslli 5}}