Pinned Repositories
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.
frankenfit
A Python library for creating, fitting, and applying predictive data modeling pipelines.
GloVe
GloVe model for distributed word representation
jaronowitz.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
pandas_exercises
Practice your pandas skills!
poisson_glmm
Testing if misspecified model (assuming independent data) recovers true parameter vector for a poisson_glmm
pymc-examples
Examples of PyMC3 models, including a library of Jupyter notebooks.
simanneal
Python module for Simulated Annealing optimization
sparse_recovery
noiseless/nonnegative sparse recovery and feature retrieval via compressed sensing
text_embedding
utility class for building/evaluating document representations
jaronowitz's Repositories
jaronowitz/GloVe
GloVe model for distributed word representation
jaronowitz/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.
jaronowitz/frankenfit
A Python library for creating, fitting, and applying predictive data modeling pipelines.
jaronowitz/jaronowitz.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
jaronowitz/pandas_exercises
Practice your pandas skills!
jaronowitz/poisson_glmm
Testing if misspecified model (assuming independent data) recovers true parameter vector for a poisson_glmm
jaronowitz/pymc-examples
Examples of PyMC3 models, including a library of Jupyter notebooks.
jaronowitz/simanneal
Python module for Simulated Annealing optimization
jaronowitz/sparse_recovery
noiseless/nonnegative sparse recovery and feature retrieval via compressed sensing
jaronowitz/text_embedding
utility class for building/evaluating document representations