University courseworkMachine Learning — LabsGroup project

Machine Learning labs

From transactional feature engineering to regression, classification, clustering, association rules and neural nets

Problem

Guided course exercises.

Card transactions and clients, advertising, credit, breast cancer, Social Network Ads, 50 Startups, Air Passengers, groceries, house prices.

Client-month base table and monthly features (Lab 2)
Logistic regression, decision tree, Naive Bayes, KNN (Labs 2.1–2.4)
Linear regression, ARIMA/SARIMAX, Random Forest with oversampling (Labs 3.1–3.3)
K-Means, PCA, Apriori (Labs 4.1–4.3)
Neural network for house prices (Lab 5.1)

Pythonpandasscikit-learnstatsmodelsmlxtendapyoriKerasDatabricks

University work; no claim of sole individual authorship.