Causal inference

shipped a readmission-prediction model in early 2024. This can be a composite case drawn from patterns documented by Hernán & Robins in , but every detail maps to real deployment failures.  Accuracy on the held-out test...

If you've studied causal inference before, you most likely have already got a solid idea of the basics, just like the potential outcomes framework, propensity rating matching, and basic difference-in-differences. Nonetheless, foundational methods often...

: Limitations of Machine Learning As an information scientist in today’s digital age, it's essential to be equipped to reply quite a lot of questions that go far beyond easy pattern recognition. Typical machine learning...

A store’s assortment is a whole and varied range of products sold to customers. It's subject to evolve based on various aspects corresponding to: economic conditions, consumer trends, profitability, quality or compliance issues, renewal...

You’re an avid data scientist and experimenter. You already know that randomisation is the summit of Mount Evidence Credibility, and you furthermore mght know that when you may’t randomise, you resort to observational data...

Large language models (LLMs) like OpenAI’s o3, Google’s Gemini 2.0, and DeepSeek’s R1 have shown remarkable progress in tackling complex problems, generating human-like text, and even writing code with precision. These advanced LLMs are...

Introduction You’ve probably heard these sayings several times, but do they really delay once we have a look at the info? In this text series, I need to take popular myths/sayings and put...

By studying changes in gene expression, researchers find out how cells function...