joongchan1's repositories
ABM
FIM individual research phase, 2022
abm_water_canal
Create an ABM Water Canal in Python
Academy-Course-SFI32064
Supporting material for the Open Risk Academy course: An introduction to Input-Output Economic Models using Python
AMES-V5.0
AMES V5.0 is a version of the AMES Wholesale Power Market Test Bed. It models salient features of U.S RTO/ISO-managed wholesale power markets operating over a high-voltage transmission grid during successive days.
ASAM
Ancillary Services Acquisition Model (ASAM) - Agent-based model to simulate processes of ancillary services acquisition and electricity markets
autogen
Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ
awesome-computational-social-science
A list of awesome resources for Computational Social Science
BehavioralDataAnalysis
Support files for the O'Reilly book "Behavioral Data Analysis with R and Python" by Florent Buisson
Causal-Inference-and-Discovery-in-Python
Causal Inference and Discovery in Python by Packt Publishing
concordia
A library for generative social simulation
Data_Analytics
A repository with common tips and tricks on data analytics
data_science_course
Introduction to data science (for not yet scientists)
dolo.py
Economic modelling in python
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.
EASYMORE
EASYMORE; EArth SYstem MOdeling REmapper
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
geospatial_course_unitn
repository with code and documentation for the course "Geospatial analysis and representation for data science" for the students in data science of the university of Trento
looper
A resource list for causality in statistics, data science and physics
MSE_Spring2024
The materials for the Spring Mathematics in Materials course at the UTK MSE
oggm
Open Global Glacier Model
pomato
Power Market Tool for the comprehensive analyses of modern electricity markets (Python+Julia)
pymrio
Multi-Regional Input-Output Analysis in Python.
pypsa-earth
PyPSA-Earth: A flexible Python-based open optimisation model to study energy system futures around the world.
quant_py
파이썬을 이용한 퀀트 투자 포트폴리오 만들기
Resources
Inventory of all the educational content that I share on spatial data analytics, geostatistics and machine learning. I hope these resources are helpful, Prof. Michael Pyrcz
streamlit_web_deploy
streamlit web 배포 연습
transitionMatrix
Statistical analysis and visualization of state transition phenomena