Comparing things: The Bayesian approach, by Michał Oleszak

Non-linear regression: basis expansion, polynomials & splines, by Michał Oleszak

Model Optimization with TensorFlow, by Michał Oleszak

Michał Oleszak – Medium

Monte Carlo Dropout Towards Data Science

Monte Carlo Dropout Towards Data Science

Estimating Performance of Regression Models Without Ground-Truth, by Michał Oleszak

SVM Kernels: What Do They Actually Do?, by Michał Oleszak

Estimating the state of the economy with finite-mixture models and the EM algorithm, by Michał Oleszak

Comparing things: The Bayesian approach, by Michał Oleszak

Useful Probability Distributions With Data Science Problems

List: Py causal ML, Curated by Ivano Bison

Explainable Boosting Machines. Keeping accuracy high while getting…, by Michał Oleszak

Drift in Machine Learning: How to Identify Issues Before You Have a Problem

What are three approaches for variable selection and when to use which, by SangGyu An, CodeX

Regression monitoring without ground-truth