juisen Goto Github PK

academic-kickstart

admission-prediction-with-pyspark-ml-using-kaggle-dataset

advanced-did

bacondecomp

:exclamation: This is a read-only mirror of the CRAN R package repository. bacondecomp — Goodman-Bacon Decomposition

boston-housing-pridiction

Published originally in 1978, in a paper titled `Hedonic prices and the demand for clean air’, this data set contains the data collected by the U.S Census Service for housing in Boston, Massachusetts. It was collected for a study that aimed at ascertaining if the availability of clean air influenced the value of houses in Boston. With only 506 rows and 14 columns, this is a small data set that seeks the discovery of ideal explanatory variables. It is very popular in pattern recognition literature and serves as a regression analysis problem. Objective: Predict the median value of occupied homes.

counterfactual-recurrent-network

Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. Bica, A. M. Alaa, J. Jordon, M. van der Schaar

credit-risk-modeling-using-kaggle-dataset

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

data-analysis-using-pyspark

dd

Tools to estimate difference-in-differences models with leads and lags in R

did

Difference in Differences with Multiple Periods and Variation in Treatment Timing

did-1

Keeping track of what is going on with the latest DiD innovations.

dmlmt

Double Machine Learning for Multiple Treatments

donskerclass.github.io

doubleml-for-py

DoubleML - Double Machine Learning in Python

doubleml-python

dyntreat

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.

econometrics-sandbox

This repository contains the code that creates the dashboards references in the “Econometrics Sandbox” blogpost series publish in the Development Impact blog (https://blogs.worldbank.org/impactevaluations)

eventstudy

A simple repo for conducting event study in finance

eventstudy-1

Event Study package is an open-source python project created to facilitate the computation of financial event study analysis.

eventstudy-2

R package and guide for performing event studies with heterogeneous dynamic effects.

hedonic

Quick example of using linear regression for real estate valuation

hedonic_price_modeling

Multivariate Linear Regression

helsinkiregion_housingprediction

Training the Helsinki region apartment databse via hedonic regression and neural network model

hpir

House Price Indexes in R

ibmstatistics

Statistics for Data Science with Python

intro-to-data-science-in-python

Repo for the first course of the Applied Data Science with Python Specialization taught by University of Michigan hosted by Coursera

mixtape

Data and Program files for Causal Inference: The Mixtape

project-for-time-series-analysis