End to end examples with MLJ

These are examples that are meant to show how MLJ can be used from loading data to producing a model. They assume familiarity with Machine Learning and MLJ.

Note that these tutorials are not meant to teach you ML or Data Science; there may be better ways to analyse the data, the primary aim is to show quick analysis so that you can get more familiar with using MLJ.

The examples can be followed in any order, the tags can guide you as to which tutorials you may want to look at first.

• Telco Churn (MLJ for Data Scientists in Two Hours), intermediate, classification, one-hot, ROC curves, confusion matrices, feature importance, feature selection, controlling iteration, tree booster, hyper-parameter optimization (tuning).

• AMES, simple, regression, one-hot, learning network, tuning, deterministic

• Wine, simple, classification, standardizer, PCA, knn, multinomial, pipeline

• Crabs XGB, simple, classification, xg-boost, tuning

• Horse, simple, classification, scientific type and autotype, missing values, imputation, one-hot, tuning

• King County Houses, simple, regression, scientific type, tuning, xg-boost

• Airfoil, simple, regression, random forest

• Boston LGBM, intermediate, regression, LightGBM

• Boston Flux, intermediate, regression, Flux, Neural Network

• Using GLM.jl, simple, regression

• Power Generation, simple, feature pre-processing, regression, temporal data

• Breast cancer, simple, model comparisons, binary classification