Three mini-challenges from the Basics of Machine Learning module, each tackling a different core ML problem type from data exploration through to modeling.
The first challenge predicts the age of abalones (a shellfish) from physical measurements, comparing linear and regularized regression models and examining which features carry the most signal. The second builds a multiclass classifier to diagnose exotic diseases from patient blood-test symptoms, working through class imbalance and symptom correlation in a medical dataset. The third implements a movie recommender system from scratch, factorizing a user-item rating matrix into user and movie latent factors as a custom Scikit-learn estimator.
Across all three, the algorithms are implemented from array operations rather than relying on prebuilt modeling libraries.