This is your work, valued

Sungho Lee

Intermediate
@slee1009

responsible-ai-toolbox. This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

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presentations. A central repository of Business Science presentations

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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.

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pystan. PyStan, the Python interface to Stan

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amazon-sagemaker-examples. Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

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Probabilistic-Programming-and-Bayesian-Methods-for-Hackers. aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

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introduction_to_ml_with_python. "파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드

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showwhy. TypeScript

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PowerBI-Planner. A Power BI template file that imports plans exported from Microsoft Planner

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FLAML. A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

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differential-privacy. C++

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tsa-tutorial. Material for the tutorial, "Time series analysis with pandas" at T-Academy

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