Oktatás
Mesterséges neuronhálók
E-feladatgyujtemeny- 10_MegerositesesTanulas.ppt
- checkpoints.zip
- ea1_levelezo.pptx
- gcp_hasznalat.pdf
- gyak0.ipynb
- gyak04.ipynb
- gyak06.ipynb
- gyak07.ipynb
- gyak08.ipynb
- gyak09.ipynb
- gyak1.ipynb
- gyak10.ipynb
- gyak2.ipynb
- gyak3.ipynb
- gyak4_old.ipynb
- gyak5.ipynb
- gyak6.ipynb
- gyak7.ipynb
- gyak8.ipynb
- gyak9.ipynb
- kagglecatsanddogs_3367a.zip
- net_example.ipynb
- project_demo.ipynb
- tiny-shakespeare.txt
- trained.zip
Artificial neural networks and their applications
- lecture_01.pdf
- lecture_02.pdf
- lecture_03.pdf
- lecture_04.pdf
- lecture_05.pdf
- lecture_06.pdf
- lecture_07.pdf
- lecture_08.pdf
- lecture_09.pdf
- practice_02.ipynb
- practice_03.ipynb
- practice_04.ipynb
- practice_05.ipynb
- practice_06.ipynb
- practice_07.ipynb
- practice_09.ipynb
- practice_10.ipynb
- practice_11.ipynb
- project_demo.ipynb
- project_demo_en_colab.ipynb
Bevezetés a mély tanulásba
- attention_dl_seminar.pdf
- ea10_multitask.pptx
- ea11_gan.pptx
- ea1_bev.ppt
- ea2_neuron.pptx
- ea3_halo.pptx
- ea4_melyhalo_aktivaciok.pptx
- ea5_regularizacio.pptx
- ea6_conv.pptx
- ea7_opt.pptx
- ea8_rnn.pptx
- ea9_dnb.pptx
- gcp_hasznalat.pdf
- gyak1.ipynb
- gyak10.ipynb
- gyak2.ipynb
- gyak3.ipynb
- gyak4.ipynb
- gyak4_kp.pptx
- gyak5.ipynb
- gyak6.ipynb
- gyak8.ipynb
- gyak9.ipynb
- jozsefattila-utf8.txt