Kernel Methods
If you like applying Kernel Methods, every challenge here gives you a chance to practice it on a real industry brief.
- ResearchIntermediateNew
Kernel Methods vs. Deep Learning on a Tiny-Data Drug-Discovery Task
You receive (or download) 3 public ADMET datasets from MoleculeNet (e.g., BBBP, Lipophilicity, FreeSolv). For each, train both: (a) a Gaussian process with a Tanimoto kernel ove…
- Kernel Methods
- Gaussian Processes
- Neural Networks
Advanced Machine Learning - ResearchIntermediateNew
Compare Kernel Methods to Trees on a Genomics Classification Task
You receive a curated benchmark of about 12,000 labeled variants with ~120 numerical + ~40 string features. Fit kernel SVMs (RBF, polynomial, string), random forest, and XGBoost…
- Kernel Methods
- Svm
- Tree Ensembles
Statistical Machine Learning - CodeIntermediateNew
Gaussian Process Regression for Wind Farm Power Curves
You receive 12 months of 10-minute SCADA data (wind speed, air temperature, power output) for 30 representative turbines, plus the manufacturer's published curve. Fit a GP with …
- Gaussian Processes
- Kernel Methods
- Uncertainty Quantification
Probabilistic Machine Learning - AnalysisIntermediateNew
Compare Kernel SVMs and Gradient Boosting on Imbalanced Tabular Data
You receive a 220,000-row anonymized loan-default dataset with mixed numeric and categorical features and a ~6% positive class. Train and evaluate (1) an RBF-kernel SVM with pro…
- Kernel Methods
- Gradient Boosting
- Model Selection
Machine Learning Practice your coursework on real scenarios.
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