Join Keith McCormick for an in-depth discussion in this video One task, many algorithms, part of Machine Learning and AI Foundations: Classification Modeling.
- [Instructor] In mathematics and computer science,…an algorithm is an unambiguous specification…of how to solve a class of problems.…In this course, the class of problems…is binary classification,…and there's a remarkable diversity of approaches.…I've always been a fan of Tom Khabaza's…9 Laws of Data Mining,…a topic that I discuss at length…in my essential elements course.…The fourth law, no free lunch for the data miner,…states the following.…
"The right model for a given application…can only be discovered by experiment."…So when playing this game,…trial and error is going to be our method.…It's at the core of doing binary classification well.…This is really the premise of the course.…Competency at binary classification equals,…competency at all of the multiple algorithms…that are capable of binary classification.…
And in addition, you have to become competent…at using these multiple approaches,…both individually and together.…In a book called The Master Algorithm,…Pedro Demingos spins out this argument in book length.…
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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