aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A game theoretic approach to explain the output of any machine learning model.

Draw pretty maps from OpenStreetMap data! Built with osmnx +matplotlib + shapely

NYU Deep Learning Spring 2020

Create delightful software with Jupyter Notebooks

NMA Computational Neuroscience course

Notebooks about Bayesian methods for machine learning

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

A repo for the pre-course work at home exercises

Book: Introduction to Python for Computational Science and Engineering

Stanford Machine Learning course exercises implemented with scikit-learn

Tutorial for surrogate gradient learning in spiking neural networks

python version of raincloud

Jupyter notebook for Udemy course: Python data science and machine learning bootcamp

Python Framework for Saliency Modeling and Evaluation

Writing good research code

Coding exercises for Neural Data Science at CSHL in 2019

Initial repo for behavioral analyses

Study materials to write more pythonic code inspired by book Effective Python

Programming exercises and mini-projects for LSMLSDA course, summer semester 2019