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.
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Optimizing Machine Learning Performance
Ce cours fait partie de Spécialisation Machine Learning: Algorithms in the Real World
Instructeur : Anna Koop
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Il y a 4 modules dans ce cours
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.
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8 vidéos1 lecture6 devoirs1 évaluation par les pairs1 sujet de discussion
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.
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6 vidéos6 devoirs1 sujet de discussion
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.
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8 vidéos7 devoirs
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.
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9 vidéos7 devoirs1 évaluation par les pairs
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Recommandé si vous êtes intéressé(e) par Machine Learning
University of California San Diego
University of Pennsylvania
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