Join Keith McCormick for an in-depth discussion in this video Next steps, part of Machine Learning and AI Foundations: Classification Modeling.
- [Instructor] I wanna thank you for taking the course…and I really hope that you've enjoyed the material.…Now that you've completed this introductory course,…you may be wondering where to turn your attention next.…Well, two of our algorithms…were related to linear regression,…discriminant analysis and binary logistic regression.…So at some point you're gonna wanna get…a really good grounding in linear regression.…And you can certainly take my own course in the library,…Machine Learning and Artificially Intelligence Foundations…Linear Regression.…
There also happens to be a course dedicated…to the topic of logistic regression in the library…called Logistic Regression in R and Excel.…Of course, we also have learned…some machine learning algorithms,…and a couple of them in particular…would be good to pursue in additional courses.…One of them is decision trees,…and I actually have two courses on decision trees…right here in the library.…The first is Machine Learning and AI Foundations…Decision Trees,…and the second is Advanced Decision Trees.…
Note: These tutorials are focused on the theory and practical application of binary classification algorithms. No software is required to follow along with the course.
- Why do you need classification?
- Statistical algorithms versus machine learning algorithms
- Combining models using ensembles
- Classification modeling challenges
Skill Level Intermediate
SPSS Statistics Essential Trainingwith Barton Poulson4h 57m Beginner
Machine Learning and AI Foundations: Recommendationswith Adam Geitgey58m 7s Intermediate
1. The Big Picture: Defining Your Classification Strategy
2. How Do I Choose a "Winner"?
3. Algorithms on Parade
4. Common Modeling Challenges
Next steps3m 17s
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