Applied machine learning
Undergraduate · Data science
Syllabus focus
Standard syllabus · STEM / applied
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$60.00 · 60 min · Undergraduate · Online ($60/hr)
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Topics typically covered
Standard syllabus
- Train/validation/test splits and cross-validation
- Linear models, trees, and ensembles as taught
- Classification metrics and calibration (intro)
- Feature processing and leakage
- Intro clustering or unsupervised methods if in the syllabus
- Ethics and limitation notes as required by the course
STEM / applied
- scikit-learn, R, or the course library
- Reading model output and error analysis
- Project and exam support
Notes
Theoretical ML and proofs live under CS / Programming where listed.