Pinned Repositories
100-pandas-puzzles
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
causalml
Uplift modeling and causal inference with machine learning algorithms
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.
nlp_course
YSDA course in Natural Language Processing
numpy-100
100 numpy exercises (with solutions)
Practical_DL
DL course co-developed by YSDA, HSE and Skoltech
dePaco's Repositories
dePaco/100-pandas-puzzles
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
dePaco/causalml
Uplift modeling and causal inference with machine learning algorithms
dePaco/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.
dePaco/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.
dePaco/nlp_course
YSDA course in Natural Language Processing
dePaco/numpy-100
100 numpy exercises (with solutions)
dePaco/Practical_DL
DL course co-developed by YSDA, HSE and Skoltech