| day |
topic |
who |
slides |
resources |
| Oct 14 |
Administrativa |
HS |
pdf |
|
|
Naive Bayes I |
HS |
4viewing 4printing
| vulgarity
classifier fail |
|
|
|
|
Weka (includes Naive Bayes) |
|
|
|
|
Reuters-21578 |
| |
Introduction: Welcome |
AN |
|
|
| |
Introduction: Supervised learning |
AN |
|
|
| |
Tutorial |
DK |
pdf |
|
| Oct 21 |
Naive Bayes II |
HS |
pdf |
|
|
Projects |
HS |
pdf |
|
| |
Introduction: What is machine learning? |
AN |
|
|
| |
Introduction: Unsupervised learning |
AN |
|
|
| Oct 28 |
Naive Bayes III |
HS |
pdf |
|
| |
LinR, one variable: Model representation |
AN |
|
|
| Nov 4 |
SVMs |
HS |
4viewing 4printing |
|
| |
LinR, one variable: Cost function |
AN |
|
|
| |
LinR, one variable: Cost function intuition I |
AN |
|
|
| |
LinR, one variable: Cost function intuition II |
AN |
|
|
| Nov 11 |
Decision trees |
HS |
pdf |
|
|
Coreference resolution |
|
|
|
| |
Linear algebra review |
AN |
|
|
| Nov 18 |
Smoothing and language models |
IS |
| |
| |
LinR with one variable: Gradient descent |
AN |
|
|
| |
LinR with one variable: Gradient descent intuition |
AN |
|
|
| |
LinR with one variable: Gradient descent for LinR |
AN |
|
|
| Nov 25 |
Decision trees |
HS |
pdf |
|
|
Coreference resolution |
|
|
|
| |
Multivariate regression: Multiple Features |
AN |
|
|
| |
Multivariate regression: Gradient Descent for Multiple Variables |
AN |
|
|
| |
Multivariate regression: Gradient Descent in Practice I |
AN |
|
|
| |
Multivariate regression: Gradient Descent in Practice II |
AN |
|
|
| Dec 2 |
Representation learning |
HS |
pdf |
|
| |
Multivariate regression: Features and polynomial regression |
AN |
|
|
| |
Multivariate regression: Normal equation |
AN |
|
|
| |
Multivariate regression: Normal equation noninvertibility |
AN |
|
|
| Dec 9 |
Tensors in NLP |
KK |
| |
| Dec 16 |
Relation classification |
HA |
| |
| Dec 23 |
Maxent classifiers |
HS |
pdf
| |
| |
LogR: Classification |
AN |
|
|
| |
LogR: Hypothesis representation |
AN |
|
|
| |
LogR: Decision boundary |
AN |
|
|
| Jan 13 |
Embeddings |
HS |
| |
| Jan 20 |
Recurrent neural networks |
DK |
| |
| Jan 27 |
Project reports |
Deyringer |
09:30
| |
|
|
Siilivask |
09:50
| |
|
|
Wurst |
10:10
| |
|
|
Eder |
10:30
| |
|
|
Baiter |
10:50
| |
| Feb 3 |
Project reports |
Schaetz |
09:30
| |
|
|
Moiseeva |
09:50
| |
|
|
Pfingstag |
10:10
| |
|
|
Herteis |
10:30
| |
|
|
Simbeck |
10:50
| |
