110 lines
3.7 KiB
Plaintext
110 lines
3.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"<div class=\"alert alert-block alert-info\">\n",
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"<h1> Ekstrakcja informacji </h1>\n",
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"<h2> 0. <i>Informacje na temat przedmiotu</i> [ćwiczenia]</h2> \n",
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"<h3> Jakub Pokrywka (2022)</h3>\n",
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"</div>\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Informacje ogólne"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Kontakt z prowadzącym\n",
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"\n",
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"prowadzący: mgr inż. Jakub Pokrywka\n",
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"\n",
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"Najlepiej kontaktowąć się ze mną przez MS TEAMS prywatnych wiadomościach lub mailowo jp40407@st.amu.edu.pl. Odpisuję co 2-3 dni. Można też umówić się stacjonarnie, na zdzwonko w godzinach dyżuru (wt 12.00-13.00) lub umówić się w innym terminie.\n",
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"\n",
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"\n",
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"## Literatura\n",
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"Polecana literatura do przedmiotu:\n",
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"\n",
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"- Koehn, P. (2009). Statistical Machine Translation. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511815829\n",
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"- Philipp Koehn. \"Neural Machine Translation\". 2020.\n",
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"- https://web.stanford.edu/~jurafsky/slp3/3.pdf\n",
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"- Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. North American Association for Computational Linguistics (NAACL).\n",
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"- Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research vol 21, number 140, pages 1-67.\n",
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"- Radford, Alec and Wu, Jeff and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya. 2019. Language Models are Unsupervised Multitask Learners\n",
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"- https://jalammar.github.io/illustrated-transformer/\n",
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"- https://www.youtube.com/watch?v=-9evrZnBorM&ab_channel=YannicKilcher\n",
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"- https://www.youtube.com/watch?v=u1_qMdb0kYU&ab_channel=YannicKilcher\n",
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"\n",
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"\n",
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"\n",
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"## Zaliczenie\n",
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"\n",
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"\n",
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"\n",
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"Do zdobycia będzie conajmniej 600 punktów.\n",
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"\n",
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"Ocena:\n",
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"\n",
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"- -299 — 2\n",
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"\n",
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"- 300-349 — 3\n",
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"\n",
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"- 350-399 — 3+\n",
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"\n",
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"- 400-449 — 4\n",
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"\n",
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"- 450—499 — 4+\n",
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"\n",
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"- 500- — 5\n",
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"\n",
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"\n",
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"**Żeby zaliczyć przedmiot należy pojawiać się na laboratoriach. Maksymalna liczba nieobecności to 3. Obecność będę sprawdzał co zajęcia. Jeżeli kogoś nie będzie więcej niż 3 razy, to nie będzie miał zaliczonego przedmiotu** \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"author": "Jakub Pokrywka",
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"email": "kubapok@wmi.amu.edu.pl",
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"lang": "pl",
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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},
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"subtitle": "0.Informacje na temat przedmiotu[ćwiczenia]",
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"title": "Ekstrakcja informacji",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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