| 20 | | We will build a simple language model (skip-gram) which has very interesting properties. When trained properly, the vectors of words obey simple space arithmetics, e.g. |
| 21 | | vector "king" − vector "man" + vector "woman" ~= vector "queen". |
| 22 | | We will train this model on a large Czech and English corpora and evaluate the results. |
| | 20 | We will build a simple character-based language model and generate naturally-looking sentences. We need a plain text and fast suffix sorting algorithm (mksary). |
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| | 25 | === Task === |
| | 26 | |
| | 27 | Change the training process and the generating process to generate the most naturally-looking sentences. Either by |
| | 28 | * pre-processing the input plain text or |
| | 29 | * setting training parameters or |
| | 30 | * changing generating process |
| | 31 | * or all above. |
