안녕하세요. 데이크루 4기 반박자😎 팀입니다.
저희 팀은 PBL 주제를 "반도체 박막 두께 분석"으로 선정했습니다.
자료를 통해 배우는 전체 과정의 학습목표는 다음과 같습니다.

 " 반도체 박막 두께를 예측하는 문제를 해결하는 과정에서 DNN 모델과 ML 모델들을 이해한다.

 또한, 각 모델을 최적화하여 성능을 향상시키는 방법을 익히고, 고급 데이터분석 기법을 통해
  경진대회에서 상위권을 노릴 수 있는 분석모델 구축 방법에 대해 배운다.  "

첫번째 스테이지에서는 분석 목표를 이해하고 데이터를 간단하게 살펴보는 과정을 실습합니다.
 
🔔본 포스팅은 데이콘 서포터즈 "데이크루" 4기 활동으로 작성되었음을 알립니다.🔔

[Stage 1]  분석 목표의 이해와 데이터 확인  https://dacon.io/competitions/official/236047/codeshare/7491
[Stage 2]  심층 신경망 모델의 이해와 활용   https://dacon.io/competitions/official/236047/codeshare/7609
[Stage 3]  심층 신경망 모델 학습결과 분석   https://dacon.io/competitions/official/236047/codeshare/7621
[Stage 4]  심층 신경망 모델의 성능 향상  https://dacon.io/competitions/official/236047/codeshare/7623
[Stage 5]  Machine Learning 회귀 모델의 이해와 활용  https://dacon.io/competitions/official/236047/codeshare/7659
[Stage 6] 고급 데이터 사이언스 기법의 이해와 활용  https://dacon.io/competitions/official/236047/codeshare/7689