Bakai Baiazbekov's repositories
dl_cmu_content
Course content repository
Advanced_Seminar_in_Empirical_International-Trade
Seminar Paper
Behavioral_Economics_Theory
Seminar Paper
BMW-Anonymization-API
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
Causal_Inference_and_Policy_Evaluation
Current working on Causal Inference
Data-Science--Cheat-Sheet
Cheat Sheets
Data-Science-Olympics-2019
My submission to the DSO2019 competition https://www.datascience-olympics.com/
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.
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.
EconometricsWithR
đź“–An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
Kaggle_HSE24
R script abt HSE24 kaggle competition
LearningX
Deep & Classical Reinforcement Learning + Machine Learning Examples in Python
tweet-conf-dash
A shiny twitter conference dashboard
unsorted
classify unsorted items based on model created with sorted items