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Introduction to Machine Learning for Artificial Intelligence End Certificate
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Introduction to Machine Learning for Artificial Intelligence
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Field Engineering (Computers & Communication)
Operating Institute Operating Institute KYUNG HEE UNIVERSITY Go to the operating agency Opens new window
Week Week 8 Week
Course Registration Period Course Registration Period 23.01.27 ~ 23.02.08
Phone Number Phone Number 031-201-3951
Course Satisfaction 4.4
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Difficulty Difficulty -
Certificate Certificate Unissued
Learning recognition time Learning recognition time 8Hour 00Minute (08Hour 28Minute)
Course Duration Course Duration 23.01.31 ~ 23.03.28
Subtitle language -
Course language 한국어(ko)
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List of participating institutions
Course Introduction
인공지능을 위한 기계학습의 의미와 이를 가능하게 하는 기계학습 모델을 만드는 기술과 모델 성능 평가 방법에 대한 이해를 위한 과목 입니다.
학습 목표
1) 인공지능을 위한 기초적인 기계학습의 개념과 핵심 구성 요소에 대해서 이해를 합니다.2) 기초적인 선형대수를 통해 기계학습에서 자주 사용되고 있는 수학적 표현에 대해서 학습합니다.
3) 파이썬(Python) 프로그래밍을 통한 기본 데이터 처리 방법과 기계학습 모델을 생성하기 위한 과정에 대해서 학습합니다.
4) 기계학습 모델을 구현할 수 있는 방법을 익히고 다양한 성능 지표를 이용하여 모델의 성능을 평가하는 방법에 대해서 이해를 합니다.
| 목차 | 세부 목차 | |
|---|---|---|
| 1 | 기계학습 개요 | 1. 기계학습 소개 I |
| 2. 기계학습 소개 II | ||
| 3. 기계학습 핵심 요소 | ||
| 2 | 기계학습 수학적 표현 | 1. 데이터 표현 |
| 2. 벡터 임베딩 | ||
| 3. 차원 축소 | ||
| 3 | 기계학습 데이터 처리 | 1. NumPy 라이브러리 |
| 2. NumPy 배열 생성, 인덱싱 및 Broadcasting | ||
| 3. 기계학습 Workflow, Pandas 라이브러리+ | ||
| 4 | 기계학습 모델 생성 과정 및 구현 | 1. Scikit-Learn 라이브러리 |
| 2. Data Stratification & Scaling | ||
| 3. Data Normalization | ||
| 4. Transformer API & Scikit-Learn Pipeline | ||
| 5 | 기계학습 모델의 복잡성 | 1. 과소적합, 과대적합 |
| 2. Bias와 Variance | ||
| 3. Bias와 Variance의 수학적 표현 | ||
| 4. Bias-Variance와 과소적합-과대적합과의 연관성 | ||
| 6 | 기계학습 모델 | 1. Decision Trees |
| 2. Random Forests | ||
| 7 | 기계학습 모델 평가 | 1. Confusion Matrix |
| 2. Precision, Recall, F1-score | ||
| 3. P-R Curve, ROC Curve | ||
| 4. Average Precision, AUC | ||
| 8 | 종합 평가 | |
책임교수
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|
담당조교
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|
이수/평가정보
| 구분 | 퀴즈(7) | 종합평가(1) |
| 반영비율 | 40% | 60% |
Q1. 수강 중 궁금한 것은 어떻게 해야 하나요?
- 수강 중 궁금한 부분은 교과목 내 [질의응답] 게시판에 작성해 주시면 담당 TA가 확인 후, 1~2일내 응답할 예정입니다.
Q2. 이수증은 언제 발급 되나요?
- 이수증은 수업이 종료되고 나서 성적처리가 완료된 후, 10~15일 이내 발급될 예정입니다.
Field Engineering (Computers & Communication)
Difficulty Difficulty -
Operating Institute KYUNG HEE UNIVERSITY Go to the operating agencyOpens new window
Certificate Certificate Unissued
Week Week 8 Week
Learning recognition time Learning recognition time 8Hour 00Minute (08Hour 28Minute)
Course Registration Period Course Registration Period 23.01.27 ~ 23.02.08
Course Duration Course Duration 23.01.31 ~ 23.03.28
Phone Number Phone Number 031-201-3951
Subtitle language -
Course language 한국어(ko)
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