Christoph Molnar
christophM
Interpretable Machine Learning researcher. Author of Interpretable Machine Learning Book: https://christophm.github.io/interpretable-ml-book/
Munich
Peter Norvig
norvig
Author, Programmer, Teacher, Research Director at Google
Google Palo Alto, CA, USA
Joaquín Amat Rodrigo
JoaquinAmatRodrigo
Data science, forecasting, statistics and machine learning.
Spain
Executable Books
executablebooks
An open collaboration to create executable books with Jupyter
Humphrey Yang
HumphreyYang
PhD candidate in Economics at ANU. Research Assistant at QuantEcon. Ex-RA at CSIRO's Data61 and RSFAS ANU.
Canberra
Christopher Rackauckas
ChrisRackauckas
Applied Mathematics Instructor at MIT, researching numerical differential equations and their applications to scientific machine learning (SciML)
Massachusetts Institute of Technology Cambridge, MA
Shu Hu
shlff
Economics PhD candidate at ANU, Developer at @QuantEcon
@QuantEcon and the Australian National University Canberra, Australia
Smit Lunagariya
Smit-create
SWE @google | Ex-Intern @google, @gsitechnology, @scipy | GSoC '20 @sympy | Mathematics and Computing | IIT-BHU, Varanasi
Google San Francisco Bay Area
John Stachurski
jstac
Researcher in stochastic dynamics and optimization, comp econ OG, part time code monkey, cofounder of @QuantEcon
Australian National University Canberra Australia