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Update 'pages/students/2016/maros_harahus/README.md'

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@ -24,6 +24,7 @@ Stretnutie 17.1.2022
- Zlepšený konvolučný autoenkóder - dosahuje state-of-the-art.
- Prečítané niečo o transformers a word2vec.
Poznámky k porade 17.1.2022:
Prezentácia Lukáš:
@ -34,6 +35,14 @@ vytvorenie "zhustenej" reprezentácie dát - (deep) autoenkóder + LSTM.
- tavba je časovo závislý proces.
- cieľom je vytvorenie modelu - "zhustenej reprezentácie" na predpovedanie rôznych veličín. Predpovedný model je možné použiť na optima
Niekoľko odkazov:
- https://thermocalc.com/academia/free-educational-package/
- https://reader.elsevier.com/reader/sd/pii/S2352492820302178?token=5EA4D3B31E698BEEAE4DB08361F9F985EC80CAF012A4EE2E8EF11479A93BE1F14C1023E529FFE200659FE8A452345596&originRegion=eu-west-1&originCreation=20220117153447
- Sandip Barui, Sankha Mukherjee, Amiy Srivastava, Kinnor Chattopadhyay : Understanding Dephosphorization in Basic OxygenFurnaces (BOFs) Using Data DrivenModeling Techniques
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