Getting started withΒ dbt
A practical guide to building, testing, and documenting SQL transformations
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A practical guide to building, testing, and documenting SQL transformations
The post Getting started withΒ dbt appeared first on Towards Data Science.
How to catch a payload that looks correct but isn't, using a watchdog pattern with working Python.
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Why the standard groupBy function isnβtΒ enough
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What each one solves, and runnable code you can paste into a notebook.
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What I learned after thinking more carefully about Structured Outputs on messy, incomplete data
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How to run the backend locally with Docker or in the cloud
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What a final-year project taught me about the gap between evaluation metrics and production decisions
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A practical guide to getting better code, not just more code
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Bagging hits a wall no amount of trees can break β here's the equation that explains why, and the experiment that proves it
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For years, a Python developer who needed a GPU had two realistic choices: Learn NVIDIA CUDA C++ well enough to write an extension, set up a build toolchain, and maintain bindings back to Python, which most people never did; or move up the stack and let someone elseβs library do it, namely PyTorch, CuPy, or RAPIDS. The second option is why the Python GPU ecosystem thrives. But it has limits.
From Kaplan-Meier curves to hazard ratios with runnable Python Code throughout
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A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training
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From Kaplan-Meier curves to hazard ratios with runnable Python Code throughout
The post Survival Analysis and the Cox Proportional Hazards Model: A Beginner-Friendly Guide appeared first on Towards Data Science.
A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training
The post Estimating from No Data: Deriving a Continuous Score from Categories appeared first on Towards Data Science.
A controlled comparison of a top-5 RAG pipeline and a full 127,000 token prompt on the same 12 questions, same system prompt and same model. Graded blind on correctness, completeness and grounding.
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Conceptual overview and walkthrough of a solution approach in Python
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A small experiment in remote SQL execution
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A preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points of R squared it cheated its way to
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Can a language model do live adversarial level design? Yes, emphasis on the adversarial part
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A reproducible Lagos case study with population data, transport access, and airspace constraints
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