samcarlos

pRotectionism

An R package dedicated to bringing protectionist policies to your code

publication_data

Publication datasets

mr_uplift

Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and multiple responses

luftwaffe_locations

A WW2 Infographic that displays the Luftwaffe locations and losses throughout the war

scgen

Single cell perturbation prediction

pewtils

General programming utilities from Pew Research Center

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.

causallib

A Python package for modular causal inference analysis and model evaluations

walker

Bayesian Generalized Linear Models with Time-Varying Coefficients

evalITR

R Package for Evaluating Individualized Treatment Rules

awesome-causality-algorithms

An index of algorithms for learning causality with data

ART-Forum-2017-Stan-Tutorial

Materials from tutorial "Using Stan to Estimate Hierarchical Bayes Models," ART Forum 2017

hete

Heterogeneous Treatment Effects

DeepReinforcementLearning

A replica of the AlphaZero methodology for deep reinforcement learning in Python

BayesianRNN

Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"

acceleratoRs

Data science and AI solution accelerator suite that provides templates for prototyping, reporting, and presenting data science analytics of specific domains

cardepreciation

car depreciation

keras-filter-visualization

Visualizing filters by finding images that maximize their outputs

online-hdp

Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.

edward

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

sense2vec

🦆 Contextually-keyed word vectors

spaCy

💫 Industrial-strength Natural Language Processing (NLP) in Python

panss_paper

panss analysis

lime-experiments

Code for all experiments.

ggbiplot

A biplot based on ggplot2

rstan-varsel

Projection predictive input variable selection using Stan+R

predcomps

An R package for extracting understanding from predictive models

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

acw_battle_data

spacetime-vis

Sources of the book "Displaying time series, spatial and space-time data with R" (1st Edition)