This course synthesizes everything your have learned in the applied machine learning specialization. You will now walk through a complete machine learning project to prepare a machine learning maintenance roadmap. You will understand and analyze how to deal with changing data. You will also be able to identify and interpret potential unintended effects in your project. You will understand and define procedures to operationalize and maintain your applied machine learning model. By the end of this course you will have all the tools and understanding you need to confidently roll out a machine learning project and prepare to optimize it in your business context.
제공자:
Machine Learning: Algorithms in the Real World 특화 과정Alberta Machine Intelligence Institute이 강좌에 대하여
최근 조회 8,493회
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 12시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 중국어 (간체자), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 터키어, 영어, 스페인어
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 12시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 중국어 (간체자), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 터키어, 영어, 스페인어
제공자:
Alberta Machine Intelligence Institute
The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 3시간 필요
Machine Learning Strategy
This week we'll present tools for understanding the overall strategy your business needs in order to see the best returns on ML investment. From understanding the current status to navigating ownership and setting up a team, this week is about understanding applied machine learning in a successful business context.
완료하는 데 3시간 필요
8개 동영상 (총 42분), 1 개의 읽기 자료, 7 개의 테스트
8개의 동영상
ML Readiness6m
Risk Mitigation5m
Experimental Mindset5m
Build/Buy/Partner7m
Setting up a Team5m
Understanding and Communicating Change7m
Weekly Summary2m
1개의 읽기 자료
IP questions10m
6개 연습문제
ML Readiness Review10m
Risk Mitigation Review10m
Experimental Mindset Review10m
Build/Buy/Partner Review30m
Setting up a Team Review5m
Communicating Change Review5m
완료하는 데 2시간 필요
Responsible Machine Learning
This week we'll talk about the broader context of machine learning: how as developers we have responsibilities regarding how our technology will be used. Using case studies and existing frameworks we'll give you the tools to figure out your own ethical approach to realize the best outcomes while deploying machine learning in the real world.
완료하는 데 2시간 필요
6개 동영상 (총 27분)
6개의 동영상
Positive Feedback Loops & Negative Feedback Loops6m
Metric Design & Observing Behaviours6m
Secondary Effects of Optimization4m
Regulatory Concerns3m
Weekly Summary2m
6개 연습문제
AI4Good Review5m
Feedback Loops Review5m
Metric Design Review5m
Secondary effects Review5m
Regulatory Concerns Review5m
Responsible Machine Learning Review30m
완료하는 데 2시간 필요
Machine Learning in Production & Planning
An important aspect of machine learning in the real world is considering how your machine learning models are integrated with existing systems, and what effect they have on your operations. This week we'll review things you should consider as you turn QuAMs and machine learning models into operational tools.
완료하는 데 2시간 필요
8개 동영상 (총 33분)
8개의 동영상
Users Break Things3m
Time & Space complexity in production5m
When do I retrain the model?4m
Logging ML Model Versioning4m
Knowledge Transfer4m
Reporting Performance to Stakeholders4m
Weekly Summary2m
7개 연습문제
Integrating Info Systems Review5m
Complexity in Production Review5m
Retrain the Model Review5m
ML Versioning Review5m
Knowledge Transfer Review5m
Reporting to Stakeholders Review5m
Machine Learning in Production and Planning Review30m
완료하는 데 5시간 필요
Care and Feeding of your Machine Learning System
Work doesn't end just because your model is deployed! In our final week we'll go over all the things you need to consider in the context of an actual working system.
완료하는 데 5시간 필요
9개 동영상 (총 45분)
9개의 동영상
Post Deployment Challenges6m
QuAM Monitoring and Logging5m
QuAM Testing5m
QuAM Maintenance3m
QuAM Updating5m
Separating Datastack from Production3m
Dashboard Essentials & Metrics Monitoring5m
Weekly Summary1m
7개 연습문제
Post Deployment Challenges Review5m
Monitoring & Logging Review5m
Testing Review5m
Maintenance Review5m
Updating Review5m
Separating Datastack from Production Review5m
Dashboard Monitoring Review5m
Machine Learning: Algorithms in the Real World 특화 과정 정보
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
Is financial aid available?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
