- [Instructor] We're going to talk about batch scoring…versus real-time scoring.…We're going to have a particular focus…on when to choose each.…I think we're all familiar with the basic concepts,…but let's do a couple of examples.…The classic, real-time scoring situation…is something like credit card fraud.…A transaction is run, and you need near-instant feedback.…As a business traveler, not infrequently I will get…a text message from my credit card asking me…if a particular transaction was legitimate.…
The classic example of batch scoring…is traditional marketing-campaign models.…Now, of course, back in the day, and this was one…of the earliest applications of these techniques;…you would send out a mass mailing…but only to those individuals that had a high score.…Now it's more often email, but clearly what you're doing…is you're doing the entire campaign, choosing the list,…and then sending out the emails.…It's not as black and white as it first seems, however.…What's contemplate in inbound call center 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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