* class lectures
  * {{:lecture_1njc.pdf|Lecture 1 - introduction to CL course}}    
  * {{:lecture_2njc.pdf|Lecture 2 - continue with introduction}}    
  * {{:lecture_3njc.pdf|Lecture 3 - continue with introduction}}    
  * {{:lecture_4njc.pdf|Lecture 4 - linguistic background}}    
  * {{:lecture_5njc.pdf|Lecture 5 - continue with linguistic background}} 
  * {{:lecture_6njc.pdf|Lecture 6 - NL grammar hierarchies}}    
  * {{:lecture_7njc.pdf|Lecture 7 - parsing and context free grammars}} 
       *    {{:bnf.pdf|Lecture 7 continued - parsing and context free grammar example}}  
  * {{:lecture_8njc.pdf|Lecture 8 - final word on syntax?, semantics & pragmatics}}  
       *      {{:lecture_9njc1.pdf|Lecture 8a - unification-based approach to NLP}}    
  * {{:lecture_9njc11.pdf|Lecture 9 - HPSG introduction}}    
       * {{:lsa2007-class1-intro-slides.pdf|Lecture 9a - Muller & Sag HPSG introduction}}    
       * {{:hpsg1.pdf||Lecture 9b - Zhang HPSG introduction}}    
       * {{:appendix_a.pdf|Lecture 9c - Naruedomkul HPSG introduction}}    
  * {{:lecture_10njc.pdf|Lecture 10 - HPSGs - Constituent Order}}    
       * {{:lsa2007-class2-order-aux-slides.pdf|Lecture 10 - HPSGs - Constituent Order}}    
  * {{:lecture_11njc.pdf|Lecture 11 - Final HPSGs - examples of parts}}  
     * {{:english_grammar.pdf|English grammar}}  
     * {{:lexicalrules.pdf|lexical rules}}  
     * {{:lexical_rules1.pdf|lexical rules 1}}  
     * {{:types.pdf|types and features}}  
     * {{:some_universal_principles_and_grammar_rules.pdf|some universal rules}}  
     * {{:hpsg_a_synopsis.pdf|synopsis}}  
          * {{:modularhpsg.ppt|modular hpsg}}  
          * {{:modularhpsg.pdf|modular hpsg}}  
          * {{:just-in-time.ppt|just in time hpsg}} 
          * {{:01basic_idea.pdf|hpsg - basic idea}}  
          * {{:02basic_systex.pdf|hpsg - basic syntax}}  
          * {{:03consituency.pdf|hpsg - consistency}}  
          * {{:04construction.pdf|hpsg - construction}}  
          * {{:06agreement.pdf|hpsg - agreement}}  
          * {{:08dependency.pdf|hpsg - dependency}}  
          * {{:09relative_clause.pdf|hpsg - relative clause}}  
          * {{:10binding_theory.pdf|hpsg - binding theory}}  
          * {{:index1.pdf|problems with cfg's}}
  * {{:alzheimer0404n.ppt|n-gram analysis}}  
  * {{:lecture_12_statnlp.pdf|Lecture 12 - Statistical NLP Introduction}}   
          * {{:lecture02.ppt|Lecture 12+ - vector space model}}    
          * {{:lecture02-1.ppt|Lecture 12++ - more vector space model}}    
          * {{:stanford_manning14.pdf|Parsing as Search - C, Manning}}    

  * {{:cse6339-presentation_ir_vsm.pdf|Lecture 13 Farzana & Yasser's vector space model}}    
          * {{:vector_space_model-updated.ppt|Lecture 13 razieh’s vector space model}}    
          * {{:presentation.ppt|Lecture 13 vector space model - morteza zihayat}}    
          * {{:lecture_13_ir_and_vsm_.ppt|Lecture 13 alternative vector space model}}    
  * {{:nima_and_sanjay.pdf|Lecture 14 Nima & Sanjay's language modelling}}    
          * {{:lecture_14_text_classification.ppt|Lecture 14 elnaz text classification}}    
          * {{:lecture_14_text_classification_.ppt|Lecture 14 alternative text classification incomplete}}     
          * {{:text_classification_presentation.pdf|Lecture 14 alternative text classification - nadine dulisch}}   

  * {{|Lecture 15 Babanejad-Dehaki & Yang - Parser Evaluation}}    


  * {{Lecture 16 Poots and Saberi HMM}}    


  * {{:nima_and_sanjay.pdf|Lecture 14 Nima & Sanjay's language modelling}}    

  * {{:ameeta.pdf|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 - fully independent and naie bayes models}}    
  * {{:raziehn-gram_presentation.ppt|Lecture 18 razieh - n-gram models}}    
  * {{:lecture_18_ngram_models.pps.ppt|Lecture 18 bahareh - n-gram models}}    
  * {{:lecture_19_cl_-_hidden_markov_models.pdf|Lecture 19 rados - hidden markov models}}    
  * {{:hmm.ppt|Lecture 19 leah - hidden Markov models in NLP}}    
  * {{:bayesian_network.pdf|Lecture 20 Bart - Bayesian belief networks}}    
  * {{:lecture_20_bayesian-networks.ppt|Lecture 20 nariman - bayesian networks}}    
  * {{:lecture_21_probabilisticparsing.ppt|Lecture 21 dmitri - probabilistic parsing}}    
  * {{:10e-eval-2x3.pdf|Lecture 22 parser evaluation - indiana}}    

* miscellaneous lectures
  * {{:pattern.pdf|matching}}    
  * {{:fsa-re-2009.pdf|finite state machines}}    
  * {{: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 - intro to statistical MT}}
    * {{:esslli-slides-day2.pdf|esslli 2 - statistical MT, theory and praxis of decoding}} 
    * {{:esslli-slides-day3.pdf|esslli 3 - statistical MT, word alignment and phrase models}}
    * {{:esslli-slides-day4.pdf|esslli 4 - evaluation of translation quality}}
    * {{:esslli-slides-day5.pdf|esslli 5 - statistical MT, syntax based models}}