Pinned Repositories
2024-AEA-Jiao-Yang
adv-r
Advanced R: a book
Advanced-R-Solutions
Set of solutions for the Advanced R programming book
causalML-teaching
This repository consolidates my teaching material for "Causal Machine Learning".
ECON_5314G_Big_Data_Economics
This intermediate applied econometrics course covers the theoretical, computational, and statistical underpinnings of the big data analysis. (first taught at Virginia Tech in 2018)
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.
Machine-Learning-from-Theory-to-Practice
This course will introduce the student to classic machine learning algorithms and deep neural network structures. The style will be first to describe the theory and math behind algorithms and then demonstrate how to use Python to create and run the models.
man2-2023
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
rmarkdown-book
R Markdown: The Definitive Guide (to be published soon)
lewangecon's Repositories
lewangecon/stat22
Statistics for Data Science
lewangecon/man2-2023
lewangecon/causalML-teaching
This repository consolidates my teaching material for "Causal Machine Learning".
lewangecon/ECON_5314G_Big_Data_Economics
This intermediate applied econometrics course covers the theoretical, computational, and statistical underpinnings of the big data analysis. (first taught at Virginia Tech in 2018)
lewangecon/Machine-Learning-from-Theory-to-Practice
This course will introduce the student to classic machine learning algorithms and deep neural network structures. The style will be first to describe the theory and math behind algorithms and then demonstrate how to use Python to create and run the models.
lewangecon/2024-AEA-Jiao-Yang
lewangecon/ag_risk
lewangecon/Algorithmic_Trading_with_Python
This comprehensive, hands-on course provides a thorough exploration into the world of algorithmic trading, aimed at students, professionals, and enthusiasts with a basic understanding of Python programming and financial markets.
lewangecon/boyuan_zhang
lewangecon/causality
AAEC 5946: Causal Inference
lewangecon/CMDA_4984_Data_Science_for_Quantitative_Finance
This course in applied data science covers the theoretical foundations of advanced quantitative approaches in machine learning, econometrics, risk and portfolio management, algorithmic trading, and financial forecasting. (first taught at Virginia Tech in 2019)
lewangecon/Code-Horizon-markdown_course_materials
Course Materials for Code Horizons Course on Creating Reproducible Reports with R Markdown
lewangecon/comments_2024_AEA
Comments on *Like Mother, Like Child: The Earned Income Tax Credit and Gender Norms*
lewangecon/course-materials
Advanced Data Analytics in Economics
lewangecon/data_visualization
Code Horizon Course on Data Visualization
lewangecon/grf
Generalized Random Forests
lewangecon/High_Dimensional_Portfolio_Estimation
This repository contains code, models, and tools for simulating and estimating portfolios based on constant and time-varying covariance matrices.
lewangecon/IGM_weights
IGM Weights
lewangecon/Machine-Learning
Machine Learning and Causal Inference
lewangecon/Mixtape-Causal-Inference
Causal Inference Mixtape Sessions
lewangecon/Mixtape-Difference-in-Differences
Difference-in-Differences
lewangecon/Mixtape-Instrumental-Variables
Instrumental Variables Mixtape Track
lewangecon/ml4econ-lecture-notes-2023
ML for Econ (Caspi at Hebrew University of Jerusalem)
lewangecon/mobility_weights_Chicago
lewangecon/r-pkgs
Building R packages
lewangecon/reading_list_ML
lewangecon/realtime_detection
lewangecon/researc_organization
lewangecon/Shift-Share
Shift-Share Instrument Mixtape Track
lewangecon/Stanford_CML_winter23
Vasilis Syrgkanis of Stanford Notes on Causal Inference (Winter 2023)