Explore options for the frequency of model rebuild and learn how to decide which strategy one should use.
- [Instructor] So how often should you rebuild your models?…It's an important question to ask…because it has major cost implications…for the cost of the project.…One of my favorite examples to this is luggage fees.…When I first started traveling heavily many years ago,…the whole way that we handled luggage…as business travelers was very different.…Most people check their bags…and there usually weren't luggage fees.…Now checking bags is rare and luggage fees can be high.…So I think I'm stating the obvious here,…any model that was talking about business travelers…and their loyalty is going to be changed perhaps dramatically…by the addition or subtraction of variables like this,…so clearly we need to rebuild our models.…
The question is how often…because if we do it more often than we need to,…we're spending infrastructure dollars…where we don't need to spend them.…How do we think through our decision?…Well, let's be clear about what our options might be.…Let's say you're going to rebuild infrequently.…You might have a situation…
Note: This course is software agnostic. The emphasis is on strategy and planning. Examples, calculations, and software results shown are for training purposes only.
- Evaluating the proper amount of data
- Assessing data quality and quantity
- Seasonality and time alignment
- Data preparation challenges
- Data modeling challenges
- Scoring machine-learning models
- Deploying models and adjusting data prep and scoring
- Monitoring and maintenance
Skill Level Beginner
Machine Learning and AI Foundations: Recommendationswith Adam Geitgey58m 7s Intermediate
Deploying Scalable Machine Learning for Data Sciencewith Dan Sullivan1h 43m Intermediate
Defining terms1m 48s
1. The Phases of a Machine Learning Project
2. Designing a Machine Learning Dataset
3. Data Prep Challenges
4. Modeling Challenges
7. Monitoring and Maintenance
Next steps1m 1s
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