Churn Without Fragmentation: How a Party-Label Bug Reversed My Headline Finding
A data quality case study from English local elections on categorical normalisation, metric validation, and why raw labels should never define analytical groups.
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Or why what appears powerful can be methodologically fragile
The post Why Powerful Machine Learning Is Deceptively Easy appeared first on Towards Data Science.
How to make decisions when your spreadsheet is lying about the future
The post A Gentle Introduction to Stochastic Programming appeared first on Towards Data Science.
How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python
How can you validate that your variables tell a consistent risk?
The post How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python appeared first on Towards Data Science.
Why AI Engineers Are Moving Beyond LangChain to Native Agent Architectures
Frameworks accelerated the first wave of LLM apps, but production demands a different architecture.
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Ensembles of Ensembles of Ensembles: A Guide to Stacking
The best machine learning model is not one model
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Using autoresearch to optimise marketing campaigns under budget constraints
The post Let the AI Do the Experimenting appeared first on Towards Data Science.
Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning
Why learn 8 scripts when you can learn 256 bytes?
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The Essential Guide to Effectively Summarizing Massive Documents, Part 2
We have the document clusters, and it’s time to unlock their true potential! Let’s explore how to extract meaningful information from the actionable clusters.
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Introduction to Approximate Solution Methods for Reinforcement Learning
Learn about function approximation and the different choices for approximation functions
The post Introduction to Approximate Solution Methods for Reinforcement Learning appeared first on Towards Data Science.
How to Improve Claude Code Performance with Automated Testing
Learn how to get the most out of Claude Code
The post How to Improve Claude Code Performance with Automated Testing appeared first on Towards Data Science.
How to Select Variables Robustly in a Scoring Model
More variables don't make a better scoring model. Stable variables do. Here's how to find them.
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Correlation vs. Causation: Measuring True Impact with Propensity Score Matching
Learn how Propensity Score Matching uncovers true causality in observational data. By finding "statistical twins," we eliminate selection bias to reveal the real impact of your interventions and business decisions.
The post Correlation vs. Causation: Measuring True Impact with Propensity Score Match...
A short intro to scientific methodology to combat "prompt in, slop out"
The post Ivory Tower Notes: The Methodology appeared first on Towards Data Science.
Git UNDO : How to Rewrite Git History with Confidence
For any data scientist who works in a team, being able to undo Git actions can be a life saver. This practical guide will teach you all you need to know to save the day.
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I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing
The hidden cost of probabilistic outputs in systems that demand reliability
The post I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing appeared first on Towards Data Science.