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.
提供方
Machine Learning: Algorithms in the Real World 专项课程Alberta Machine Intelligence Institute课程信息
9,125 次近期查看
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完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 4 门）
可灵活调整截止日期
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完成时间大约为13 小时
英语（English）
字幕：英语（English）
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 4 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
完成时间大约为13 小时
英语（English）
字幕：英语（English）
提供方
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
教学大纲 - 您将从这门课程中学到什么
完成时间为 4 小时
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.
完成时间为 4 小时
8 个视频 （总计 42 分钟）, 1 个阅读材料, 7 个测验
8 个视频
ML Readiness6分钟
Risk Mitigation5分钟
Experimental Mindset5分钟
Build/Buy/Partner7分钟
Setting up a Team5分钟
Understanding and Communicating Change7分钟
Weekly Summary2分钟
1 个阅读材料
IP questions10分钟
6 个练习
ML Readiness Review10分钟
Risk Mitigation Review10分钟
Experimental Mindset Review10分钟
Build/Buy/Partner Review30分钟
Setting up a Team Review5分钟
Communicating Change Review5分钟
完成时间为 2 小时
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.
完成时间为 2 小时
6 个视频 （总计 27 分钟）
6 个视频
Positive Feedback Loops & Negative Feedback Loops6分钟
Metric Design & Observing Behaviours6分钟
Secondary Effects of Optimization4分钟
Regulatory Concerns3分钟
Weekly Summary2分钟
6 个练习
AI4Good Review5分钟
Feedback Loops Review5分钟
Metric Design Review5分钟
Secondary effects Review5分钟
Regulatory Concerns Review5分钟
Responsible Machine Learning Review30分钟
完成时间为 2 小时
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.
完成时间为 2 小时
8 个视频 （总计 33 分钟）
8 个视频
Users Break Things3分钟
Time & Space complexity in production5分钟
When do I retrain the model?4分钟
Logging ML Model Versioning4分钟
Knowledge Transfer4分钟
Reporting Performance to Stakeholders4分钟
Weekly Summary2分钟
7 个练习
Integrating Info Systems Review5分钟
Complexity in Production Review5分钟
Retrain the Model Review5分钟
ML Versioning Review5分钟
Knowledge Transfer Review5分钟
Reporting to Stakeholders Review5分钟
Machine Learning in Production and Planning Review30分钟
完成时间为 5 小时
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.
完成时间为 5 小时
9 个视频 （总计 45 分钟）
9 个视频
MLPL Recap9分钟
Post Deployment Challenges6分钟
QuAM Monitoring and Logging5分钟
QuAM Testing5分钟
QuAM Maintenance3分钟
QuAM Updating5分钟
Separating Datastack from Production3分钟
Dashboard Essentials & Metrics Monitoring5分钟
Weekly Summary1分钟
7 个练习
Post Deployment Challenges Review5分钟
Monitoring & Logging Review5分钟
Testing Review5分钟
Maintenance Review5分钟
Updating Review5分钟
Separating Datastack from Production Review5分钟
Dashboard Monitoring Review5分钟
关于 Machine Learning: Algorithms in the Real World 专项课程
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.
After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning.
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