Dancing with the stars of binary realms.
Exploring the classical discrete optimization problem through custom constructive heuristics and integer programming in Python Graph coloring heuristic solution for 32 nodes instance. (Image by the author). Graph coloring theory has a central position in discrete mathematics. It appears in many places
Diving into the critical concepts of unit roots and stationarity. Continue reading on Towards Data Science »
Optimizing performance using unstructured, real-world data Vardan Papikyan (Unsplash) Much has been written about the basics of Logistic Regression (LR) — its versatility, time-tested performance, even the underlying math. But knowing how to implement LR successfully and debug inevitable errors is much
As a data scientist we are occasionally faced with situations where we need to model a trend to predict future values. Whilst there is a temptation to focus on statistical or machine learning based algorithms, I am here to present
How to estimate causal effects when you cannot randomize treatment Continue reading on Towards Data Science »
The Moat for Enterprise AI is RAG + Fine Tuning — Here’s Why To succeed with generative AI at scale, we need to give LLMs the diligence they deserve. Enter RAG and fine tuning. Photo by Volodymyr Hryshchenko on Unsplash. The hype around LLMs
The ability to ask questions to your data set has always been an intriguing prospect. Continue reading on Towards Data Science »
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