Learning to Learn

https://datascienceschool.net/view-notebook/79140e6a9e364bcbb04cb8e525b9dba4/

https://unabated.tistory.com/entry/%EC%B5%9C%EB%8C%80%EC%9A%B0%EB%8F%84%EB%B2%95Maximum-Likelihood

http://blog.naver.com/PostView.nhn?blogId=sogangori&logNo=221073537958

https://reniew.github.io/17/

https://kangbk0120.github.io/articles/2018-03/information-theory

PRML , Deep Learning book 참고

My Code

def Ck_Laser(arr):
    if arr[0]=='(' and arr[1]==')':
        return True
    else:
        return False
    
def Ck_in_line(Laser_num):
    if len(Laser_num)>0:
        return True
    else:
        return False

def solution(arr):
    ans=0
    arr=list(arr)
    Laser_num=[]
    
    while arr:
        ck_L=Ck_Laser(arr)
        ck_in=Ck_in_line(Laser_num)
#         print(arr)
#         print(Laser_num)
#         print('ans:{}'.format(ans))
#         print(ck_in)
        if ck_in==False: #현재 막대기 밖에 있음
            if ck_L==True: #레이저 만나면
                for i in range(2):
                    arr.pop(0) #걍 레이저 제거
            else:
                arr.pop(0) #막대기 시작
                Laser_num.append(0) #조각 수 세기 위한 공간 할당
        else: #현재 막대기 안에 있음
            if ck_L==True: #레이저 만나면
                #현재 지나고 있는 막대기의 레이저 수 전부에 +1
                for i in range(len(Laser_num)):
                    Laser_num[i]+=1
                for i in range(2):
                    arr.pop(0) #레이저 제거
            elif arr[0]=='(':
                arr.pop(0) #막대기 시작
                Laser_num.append(0) #조각 수 세기 위한 공간 할당
            elif arr[0]==')':
                arr.pop(0)
                ans+=(Laser_num.pop()+1)
    return ans

Better Code

def solution(arrangement):
    answer = 0
    arrangement = arrangement.replace("()","L")
    stack = []
    for idx, c in enumerate(arrangement):
        if c == '(':
stack.append('(')
            answer += 1
        elif c == ')':
stack.pop()
        else:
            answer += len(stack)  #스택길이가 막대기 개수이고, 한번 레이저마다 막대기 개수만큼 조각늘어남
return answer

http://m.blog.daum.net/jungjin1980/270?tp_nil_a=1

https://www.popit.kr/%EC%9A%A9%EC%96%B4-%EC%A0%95%EB%A6%AC-%EC%9E%85%EA%B0%9C%EB%B0%9C%EC%9E%90%EB%A5%BC-%EC%9C%84%ED%95%9C-accuracy-precision-recall/

http://schoolofweb.net/blog/posts/%ED%8C%8C%EC%9D%B4%EC%8D%AC-oop-part-4-%ED%81%B4%EB%9E%98%EC%8A%A4-%EB%A9%94%EC%86%8C%EB%93%9C%EC%99%80-%EC%8A%A4%ED%83%9C%ED%8B%B1-%EB%A9%94%EC%86%8C%EB%93%9C-class-method-and-static-method/

https://datascienceschool.net/view-notebook/3bd9864b09d0466995134220f6779d6d/