Pinned Repositories
adisetyop.github.io
Website
ax-exploration
Try to explore Facebook's Ax and Pytorch
bayesian-linear-regression-bandit
Bayesian Linear Regression using different methods
bayesian-machine-learning
Notebooks related to Bayesian methods for machine learning
blog
This is my blog
CodeVersioningWorkshopHomework
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.
inference-with-pyro
Bayesian logistic regression with variational inference and Hamiltonian Monte Carlo
planout
PlanOut is a library and interpreter for designing online experiments.
Playground
adisetyop's Repositories
adisetyop/bayesian-linear-regression-bandit
Bayesian Linear Regression using different methods
adisetyop/adisetyop.github.io
Website
adisetyop/ax-exploration
Try to explore Facebook's Ax and Pytorch
adisetyop/bayesian-machine-learning
Notebooks related to Bayesian methods for machine learning
adisetyop/blog
This is my blog
adisetyop/CodeVersioningWorkshopHomework
adisetyop/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.
adisetyop/inference-with-pyro
Bayesian logistic regression with variational inference and Hamiltonian Monte Carlo
adisetyop/planout
PlanOut is a library and interpreter for designing online experiments.
adisetyop/Playground
adisetyop/worst-ad-in-adgroup
Probability calculation for least-served ad in the adgroup under automatic Google Ads rotation