pikapikapoo

causalML-teaching

This repository consolidates my teaching material for "Causal Machine Learning".

causalinference_crashcourse

Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks

awesome-causal-inference

A curated list of causal inference libraries, resources, and applications.

QuantTrading

EmpiricalIO

Causal-Inference-with-Python

Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.

pyblp

BLP Demand Estimation with Python

pyfixest

Fast High-Dimensional Fixed Effects Regression in Python following fixest-syntax

Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Efficient-Python-for-Data-Scientists

Writing clean and optimized Python code

scikit-learn-videos

Jupyter notebooks from the scikit-learn video series

Shift-Share

Shift-Share Instrument Mixtape Track taught by Peter Hull

AI-Expert-Roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2022

Machine-Learning

Machine Learning and Causal Inference taught by Brigham Frandsen

pandas-videos

Jupyter notebook and datasets from the pandas video series

optimagic

optimagic is a Python package for numerical optimization. It is a unified interface to optimizers from SciPy, NlOpt and other packages. optimagic's minimize function works just like SciPy's, so you don't have to adjust your code. You simply get more optimizers for free. On top you get diagnostic tools, parallel numerical derivatives and more.

FixedEffectModel

Fixedeffectmodel: panel data modeling in Python

Instrumental-Variables

Instrumental Variables Mixtape Track taught by Peter Hull

paris_workshop_2022

Paris Quantitative Economics Workshop 2022

da-coding-rstats

Coding course to complete Data Analysis in R

da-coding-python

This is a coding course in Python to accompany the Data Analysis material

Causal-Inference-2

Causal Inference II Mixtape Session taught by Scott Cunningham

Causal-Inference-1

Causal Inference 1 Mixtape Session taught by Scott Cunningham

causalml

Uplift modeling and causal inference with machine learning algorithms

da_case_studies

Codes for case studies for the Bekes-Kezdi Data Analysis textbook

Causalinference

Causal Inference in Python

rdrobust

Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.

BLP-Python

BLP-Python provides an implementation of random coefficient logit model of Berry, Levinsohn and Pakes (1995)

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.