머리말......................................................................................................3

제 01 장 인공지능.................................................................................................11

1.1 인공지능이란...................................................................................12
1.2 인공지능의 발전사...........................................................................14
1.3 인공지능 붐(boom)..........................................................................16
1.4 활용 응용분야..................................................................................21
1.5 최근 화제-인공지능의 장/단점.........................................................32

제 02 장 수학과 기계학습......................................................................................37

2.1 벡터................................................................................................38
2.2 곱 합 연산.......................................................................................41
2.3 행렬................................................................................................42
2.4 미분 편미분.....................................................................................43
2.5 지수 로그함수..................................................................................44
2.6 평균 분산 확률분포..........................................................................47
2.7 최적화.............................................................................................49
2.8 최적화 알고리즘..............................................................................50

제 03 장 지식표현과 기계학습................................................................................57

3.1 지식이란 무엇인가...........................................................................58
3.2 지식 베이스 구축.............................................................................60
3.3 지식과 규칙.....................................................................................62
3.4 불확실한 지식표현...........................................................................68
3.5 규칙기반 시스템..............................................................................70
3.6 기계학습.........................................................................................71

제 04 장 추론 시스템.............................................................................................77

4.1 전문가 시스템..................................................................................78
4.2 추론 엔진........................................................................................80
4.3 퍼지 추론........................................................................................81
4.4 퍼지관계 적용 알고리즘...................................................................89
4.5 인공지능 추론..................................................................................89

제 05 장 인공 신경망.............................................................................................93

5.1 뇌의 동작........................................................................................94
5.2 뉴런 계산........................................................................................95
5.3 퍼셉트론.........................................................................................98
5.4 다층 퍼셉트론................................................................................103
5.5 가속 학습......................................................................................104

제 06 장 딥 러닝.................................................................................................109

6.1 딥 러닝 등장 배경..........................................................................110
6.2 컨볼루션 신경망(CNN)...................................................................113
6.3 CNN 사례연구..............................................................................116
6.4 GAN모델......................................................................................118
6.5 딥 러닝 장단점...............................................................................121

제 07 장 학습(비지도, 준지도, 전이, 강화, 표현)...................................................125

7.1 비지도 학습과 배경........................................................................126
7.2 준지도 학습...................................................................................133
7.3 전이학습.......................................................................................138
7.4 강화 학습......................................................................................140
7.5 표현학습.......................................................................................143

제 08 장 인식......................................................................................................147

8.1 패턴인식.......................................................................................148
8.2 전처리...........................................................................................150
8.3 특징추출.......................................................................................154
8.4 매칭..............................................................................................158

제 09 장 인공지능 필기체 숫자인식 모델..............................................................165

9.1 데이터 베이스................................................................................166
9.2 동일 필기체 숫자 흡수 ..................................................................169
9.3 유사 필기체 숫자의 인공지능 적용 .................................................177
9.4 필기체 숫자 시스템 체험 연습........................................................180

제 10 장 컴퓨터 비전...........................................................................................183

10.1 영상 획득 및 표현........................................................................185
10.2 이진영상(binary image)..............................................................187
10.3 영상처리 기본 연산......................................................................188
10.4 영상분할.....................................................................................193
10.5 영상 특징(image feature)...........................................................199
10.6 컴퓨터 비전 3차원.......................................................................205
10.7 컴퓨터 영상 이해.........................................................................206

제 11 장 인공지능 자동차번호판 인식모델............................................................213

11.1 번호판 영상취득..........................................................................215
11.2 시스템 전반적 흐름 및 전처리......................................................217
11.3 번호판 인식.................................................................................224
11.4 번호판의 종류..............................................................................228
11.5 번호판 매칭.................................................................................228
11.6 인공지능 적용 접근......................................................................229

제 12 장 지능 로봇..............................................................................................235

12.1 RPA...........................................................................................237
12.2 로봇 코딩의 마음가짐...................................................................248
12.3 지능형 로봇.................................................................................251
12.4 로봇 청소기 알고리즘...................................................................256

제 13 장 인공지능 자연어 처리............................................................................261

13.1 자연어 분석 ................................................................................263
13.2 자연어 이해.................................................................................270
13.3 자연어 생성과 강화학습...............................................................271