|
DATE
|
TOPIC
|
MATERIALS
|
|
18/9
|
Natural Language Processing: Problems and perspectives |
- Slides (I.1) - [FT] - Chapter 1, Section 2.1 - Papers [Abney, 2011, Aslin, 2017] |
|
19/9
|
Introduction/Recall to/of probability calculus |
- Slides (I.2) - [FT] - Sections 2.2, 2.2.1 - [LGS] - Sections from 1.1 to 1.2.5 - Bayesian Models [Chater et. al 2010] |
|
19/9
20/9 |
N-grams Language Models Markov Models |
- Lesson Notes - [FT] - Sections 2.2.2, 2.2.3 - [SLP3] - Chapter 3 - Slides (I.3) - Paper [Rabiner, 1989] |
|
20/9 25/9 |
Introduction to Machine Learning |
- Slides (I.4). - [FT] - Section 2.3 - Paper [Emms, Luz, 2007]. |
|
25/9 26/9 |
Introduction to Deep Learning |
- Slide (I.4b). - [FT] - Chapter 3 |
| 27/9 | The evaluation of NLP applications | - Slides (I.5) - [FT] - Chapter 5 - [OHCL] Chapter 22 - EVALITA WebSite (PoS 2007) - SemEval |
REFERENCES
[FT]