Course timings 11-1150 WThF in KD103
Office hours 1500-1630 WTh in KD303. (Email me if my office is locked during that time. I'm probably close by.)
| Lecture date | Topics covered | Materials |
| Jan 5 | Introduction, course logistics, first project | Slides, Trains demo |
| Jan 6 | Project ideas (Trains, Cricinfo) | Slides, Cricinfo demo |
| Jan 11 | Probability | Slides |
| Jan 12 | Regression analysis | Slides |
| Jan 13 | Probabilistic interpretation of regression | " |
| Jan 18 | Intro to statistics | Slides |
| Jan 19 | Statistical hypothesis testing | " |
| Jan 20 | Statistics: practical considerations | " |
| Jan 21 | Granger causality | Slides, Causality demo |
| Jan 24 | Clustering | Slides |
| Feb 1 | Intro to search | - |
| Feb 2 | Boolean search | Slides |
| Feb 3 | Quiz | - |
| Feb 8 | Project presentations | - |
| Feb 9 | Ranked retrieval + project 2 intro | Slides Project code |
| Feb 10 | Language models | Slides |
| Feb 15 | Text clustering | Slides |
| Feb 16 | Befriending LDA | Slides |
| Feb 17 | Befriending LDA (continued) | - |
| Feb 22 | Search engine evaluation | Slides |
| Feb 23 | From search to discovery | Slides |
| Mar 8 | Introduction to recommender systems | Slides |
| Mar 22 | Content-based recommender systems | - |
| Mar 23 | Quiz | - |
| Mar 29 | Collaborative filtering | Slides |
| Mar 30 | Lessons from the Netflix Prize | Slides |
| Mar 31a | Knowledge-based recommenders | Slides |
| Mar 31b | Explanations in recommender systems | Slides |
| Apr 5 | Introduction to affective computing + project intro | Slides Data description Data |
| Apr 6 | Sentiment analysis | Slides |
| Apr 7a | Personality analysis | Slides |
| Apr 7b | Project presentations | - |
| Apr 7c | Project presentations | - |
| Apr 12 | Emotion detection | Slides |
| Apr 13 | New approaches to emotion detection | - |
| Apr 19 | Brain computer interfaces | Slides |
| Apr 20 | Gamification | Slides |
| Apr 21 | Staying human | Slides |
Upcoming deadlines:
Materials: Search engine book
Recommender systems handbook