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Alberta Machine Intelligence Institute

실용 머신 러닝 소개

Anna Koop

Instructor: Anna Koop

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

5 assignments

Taught in Korean

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There are 4 modules in this course

이번 주는 머신 러닝(ML)이 무엇인지 배우고, 다양한 문제 상황을 비교해보고, ML에 대해 흔히 무엇을 잘못 알고 있는지 알아볼 것입니다. 이 내용을 배우고 나면 머신 러닝 비즈니스 솔루션에 필요한 요소를 파악할 수 있습니다.

What's included

12 videos6 readings2 assignments3 discussion prompts

이번 주에는 비즈니스 니즈를 머신 러닝 문제로 변환하는 방법을 배울 것입니다. 잘 정의된 QuAM 질문을 만드는 방법을 알 수 있도록 몇 가지 적용 사례를 알아볼 겁니다. ML에 성공하려면 질문의 범위를 좁히고 학습에 필요한 데이터를 확보했는지 확인하는 것이 중요합니다!

What's included

8 videos4 readings1 assignment2 discussion prompts

이번 주는 전부 데이터에 관한 내용입니다. 데이터 수집과 학습 데이터의 다양한 출처에 대해 알아볼 것입니다. 데이터가 얼마나 필요한지, 윤리적 문제 등 어떤 실수를 하게 될 수 있는지 알아볼 것입니다.

What's included

9 videos2 readings1 assignment2 discussion prompts

이번 주는 머신 러닝 프로세스 라이프사이클(MLPL)에 대해 배울 것입니다. MLPL의 정의와 구성 요소를 이해하고 사례 연구를 통해 MLPL의 적용 사례를 분석합니다.

What's included

7 videos2 readings1 assignment2 discussion prompts

Instructor

Anna Koop
Alberta Machine Intelligence Institute
5 Courses37,352 learners

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