데이터 사이언티스트

데이터 사이언티스트를 꿈꾸는 모두에게, "논문을 읽어라"라는 말을 듣습니다.

그렇다면, 가장 읽어야하는 기초적인 논문은 무엇일까요?

 

대표적으로, 6가지를 소개하고 그것을 주1회씩 리뷰하는 블로그를 쓸 예정입니다.

 

Attention Is All You Need :https://arxiv.org/pdf/1706.03762.pdf

 

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding: https://arxiv.org/pdf/1810.04805.pdf

 

A Style-Based Generator Architecture for Generative Adversarial Networks: https://arxiv.org/pdf/1812.04948.pdf

 

 Learning Transferable Visual Models From Natural Language Supervision : https://arxiv.org/pdf/2103.00020.pdf

 

Mastering the Game of Go with Deep Neural Networks and Tree Search: https://storage.googleapis.com/deepmind-media/alphago/AlphaGoNaturePaper.pdf

 

Deep Neural Networks for YouTube Recommendations: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45530.pdf

 

 

참고 링크:https://towardsdatascience.com/6-papers-every-modern-data-scientist-must-read-1d0e708becd