BUS 696: Generative AI in Finance — Chapman University (Prof. Jonathan Hersh)

Python interactive dashboards for learning data science

well-documented demonstration Python Jupyter workflows for many common machine learning workflows

Must-read papers and resources related to causal inference and machine (deep) learning

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Materials for DataScience.com LTV and Neural Nets Talks at PyData Seattle

Streamline a data analysis process

Authoring Books and Technical Documents with R Markdown

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

Generalized Method of Moments estimation

[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"

Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.

Python implementations of contextual bandits algorithms

Generalized Random Forests

Lecture and conference materials for the DSE2024 at University of Wisconsin-Madison

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

Slides from NBER Methods Lecture (extracted from the Wayback Machine)

Repository for the ISU Causal Inference Working Group

Time series analysis is a statistical technique that is used to analyze and model time-based data. It involves identifying patterns, trends, and relationships in data that change over time, and usi…

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accur…

Metaheuristic optimization deals with optimization problems using metaheuristic algorithms. Optimization is essentially everywhere, from engineering design to economics and from holiday planning to…

A Python replication of an inventory routing problem article

Econometrics and causal inference plays an important role in technology, particularly in areas such as machine learning and artificial intelligence. In these fields, the goal is often to understand…

Jupyter notebooks for MIT 14.38 Causal Machine Learning course

Code and notebooks for my Medium blog posts

Book about interpretable machine learning