A Spark library for Amazon SageMaker.

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, …

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

Functions used for running generalized propensity score methods with a continuous treatment, where treatment is assigned at the highest level in study.

Building Convolutional Neural Networks From Scratch using NumPy

Java implementation of Q-learning with various "worlds" and experiments.

Causal Inference in Python

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1