bcecon Goto Github PK

01-postcards

02-distill-postcards

30daymapchallenge2021

My entries for the #30DayMapChallenge 2021 on Twitter

aleceng

Alec's ML project with Devon

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

bcecon.github.io

Byeong-Hak Choe's website

bds

Code and examples from Business Data Science

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

blogdown

Create Blogs and Websites with R Markdown

causal-inference-1

Causal Inference 1 Mixtape Session taught by Scott Cunningham

causal-inference-tutorial

Repository with code and slides for a tutorial on causal inference.

climate-econ

A repository for tracking developments in the climate/environmental/ecological economics literature

compecon2020

Computational Economics Course 2020 by Kenneth Judd

compecon_fall17

ECON 815: Computational Methods for Economists

corenlp

Stanford CoreNLP: A Java suite of core NLP tools.

covid-19-data

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

covid-policy-tracker

Systematic dataset of Covid-19 policy, from Oxford University

covid-vaccine-tracker-data

danl-website

data-visualization-with-python

Discover how Matplotlib and Seaborn can help clearly communicate and present your newly acquired insight

dataviz

A book covering the fundamentals of data visualization

dime-r-training

Dime Analytics R Training

doubleml-for-py

DoubleML - Double Machine Learning in Python

doubleml-for-r

DoubleML - Double Machine Learning in R

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

ds595-machine-learning-for-engineering-and-science-applications

Code and data for my class DS595 Machine Learning for Engineering and Science Applications

dscourses19

ECON 5253: Data Science for Economists, University of Oklahoma (Spring 2019)

dse2021_tutorials

dynamic-stochastic-dice

Instructions and replication code for Managing Climate Change Under Uncertainty: Recursive Integrated Assessment at an Inflection Point

ec524w20

Masters-level applied econometrics course—focusing on prediction—at the University of Oregon (EC424/524 during Winter quarter, 2020 Taught by Ed Rubin