하여 선형 회귀와 심층 신경망 회귀 모델을 모두 구축하고,전력 생산량을 예측했습니다. 그 과
정에서 설명 가능성 및 신경망의 이면에 있는 수학과 같은 주제에 관한 새로운 개념을 탐구했
습니다.
지금까지의 내용은 노코드 및 로우코드 솔루션에 관한 것이었습니다.그러나 좀 더 유연한 솔
루션이 필요한 상황이 있을 수 있습니다. 다음 장에서는 사이킷런과 케라스를 사용해 사용자
맞춤형 코드로 솔루션을 구축하는 방법을 배웁니다. 두 라이브러리 모두 매우 접근성이 좋기
때문에,
ML
에 파이썬을 어떻게 사용하면 좋을지를 탐구하는 시작점으로 매우 좋습니다.
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