Rb. Slajdovi, kod, linkovi 1. Ekspertni sistemi (07.10.2015.) 2. Mašinsko učenje – uvod Titanic: Data Preparation R script (14.10.2015.) 3. Klasifikacija (osnove) Stabla odlučivanja: Klasifikaciona stabla (21.10.2015.) —————————————————————- Classification (quick overview) Decision (classification) trees (20.10.2015) ————————————————————— Titanic: Data Preparation + Classification Trees scripts 4. Naive Bayes klasifikator (28.10.2015.) ———————————————————– Cross-validation; Bias & Variance Naive Bayes Classifier (27.10.2015) ———————————————————— Titanic: Classification Tree + Naive Bayes R scripts 5. Klasterizacija (K-Means, Expectation Maximization) (04.11.2015.) ————————————————————- Clustering (K-Means, Expectation Maximization) (03.11.2015) ————————————————————- Twitter User Clustering – R script + dataset 6. – 7. Text Mining – osnove kNN klasifikator (14. i 18.11.2015.) ——————————————————— Introduction to Text Mining (10. i 17. 11.2015) ——————————————————— TM: tweets clustering – R script + data TM: email classification – R script + data 8. Neuronske Mreze 1 Još materijala ——————————————————— Neural Networks 1 More info 9. Neuronske Mreze 2 Još materijala 10. Modeli znanja u formi semantičke mreže/grafa Analiza društvenih mreža (16.12.2015) ——————————————————— Graph-based Knowledge Bases Common sense knowledge in AI (example applications) (12.12.2015) 11. Umrežavanje podataka na Web-u (Web of Data) (23.12.2015.) ——————————————————– RDF & RDFS – Quick Intro Web of Data; RDFa, Microdata, JSON-LD (15.12.2015) 12. SPARQL upitni jezik (26.12.2015) ——————————————– SPARQL Query Language (slides) (22.12.2015) ——————————————– SPARQL examples (code) 13. Prepoznavanje entiteta u tekstu / Semantičko indeksiranje (30.12.2015.) ———————————————————————- Semantic Indexing (Entity Linking) (29.12.2015) Materijali sa predavanja iz prethodne školske godine 2014 / 2015