An interactive framework to visualize and analyze your AutoML process in real-time.

Official Code for "Non-Probability Sampling Network for Stochastic Human Trajectory Prediction (CVPR 2022)"

Faster, better, smarter ecological niche modeling and species distribution modeling

Portfolio-grade audit of a student mental health & academic pressure survey. Measures coverage and sample imbalance, runs validity checks, highlights measurement and selection bias risks, and converts messy open-text “stress causes” into a transparent taxonomy. Ships a Markdown report, figures, and a Streamlit dashboard.

Longform data analysis article arguing every “dataset” is actually three: Observed (captured rows), Missing (what should exist but doesn’t), and Excluded (what filters/joins/dropna removed). Includes dataset accounting, join-loss and missingness audits, segmentation checks, and practical templates to prevent biased KPIs and wrong conclusions.

R code used for the analyses of the paper: Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using different taxa

Pipelines to evaluate Breast Cancer Purity Score and to correct sampling bias

Efficient Multistream Classification using Direct DensIty Ratio Estimation

🚀📐 Representación gráfica de distribución de muestreos aleatorios.

Analyze and compare three distinct datasets to uncover insights about observed, missing, and excluded data for better decision-making.

📊 Evaluate survey quality and bias through coverage, representativeness, and measurement risk audits for reliable insights and data validity checks.