Browsing: Data Science
What about default values and argument extractions?from pydantic import validate_call@validate_call(validate_return=True)def add(*args: int, a: int, b: int = 4) -> int:return str(sum(args) + a + b)# —-add(4,3,4)>…
There are various modeling techniques for hierarchies. Which of them performs best in dimensional modeling in Data Warehouses? And how to address various types of hierarchies…
What can we learn from this modern problem?Photo by Igor Omilaev on UnsplashGDP is a very strong metric of a country’s economic well-being; therefore, making forecasts…
In the context of Language Models and Agentic AI, memory and grounding are both hot and emerging fields of research. And although they are often placed…
What are they and what are they notIn this article, I attempt to clarify the use of essential tools in the applied econometrician’s toolkit: Difference-in-Differences (DiD)…
The only 5-steps roadmap you need. Your new career journey starts here!11 min read·14 hours agoI’m Khouloud El Alami, a data scientist at Spotify, and I…
Part 1 – Basic Concepts and ExamplesLinear programming is a powerful optimization technique that is used to improve decision making in many domains. This is the…
Data model layers, environments, tests and data quality explainedAI generated image using KandinskyData modelling is an essential part of Data engineering. I would say this is…
Benchmarking Lag-Llama against XGBoostCliffs near Ribadesella. Photo by Enric Domas on UnsplashOn Hugging Face, there are 20 models tagged “time series” at the time of writing.…
How to address the shortcomings of shallow, outdated models and future-proof your modeling strategy11 min read·22 hours agoPhoto by Justin Chrn on UnsplashI have been involved…