Skip to content

Handouts

Full class walkthroughs as single-page documents. Each one renders every figure from the actual data, ships the code to reproduce it, and includes solved exercises.

They complement the class pages rather than replace them: each goes deep on one topic and works both as a companion during class and as a reference afterwards.

Written in Portuguese

The handouts are course material for the in-person classes and are written in Brazilian Portuguese. The code, the library names and the figures are language-independent.

  • Exploratory Data Analysis


    California Housing — 20,640 districts from the 1990 Census.

    Integrity audit, univariate analysis for numeric and categorical variables, all three pairings (numeric × numeric, categorical × numeric, categorical × categorical), multivariate and geospatial analysis. Includes an interactive skewness/kurtosis simulator.

    ~3 h · 19 figures · 10 exercises

    open

  • Normalization and Transformation


    Titanic — 891 passengers, 866 missing values.

    Missing data and the MCAR / MAR / MNAR mechanisms, a decision diagram of techniques by variable type, scaling, shape transformation, categorical encoding, and leakage measured across four scenarios.

    ~3 h · 10 figures · seven-checkpoint exercise

    open

  • Dimensionality Reduction


    Iris and MNIST — from 4 dimensions to 784.

    PCA from two derivations, how to choose k, reconstruction and interpretation. Where PCA fails on non-linear manifolds, then t-SNE and UMAP: what each one preserves, what each one distorts, and a decision rule for choosing between them. Appendix on the curse of dimensionality.

    ~3 h · 12 live simulators · eight-step Iris lab + 5 MNIST tasks

    open

  • From EDA to Dimensionality Reduction


    Palmer Penguins — 344 penguins, 6 input columns, 19 missing values from two causes.

    An in-class lab that runs the whole path end to end: univariate then bivariate analysis, a train/test split before any transformation, a pipeline that handles missing values and scaling without leaking, and the same data projected by PCA, t-SNE and UMAP — compared under a single criterion, then applied to unseen points.

    Colab notebook · 8 steps, each ending in a check value

    open in Colab

Classroom use

Each handout has an anchored sidebar index, a copy button on every code block, and its own print stylesheet — the menu, buttons and interactive elements are dropped when printing or exporting to PDF.