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Polars vs pandas: the DataFrame rewrite that changed the default
For years, the default choice for tabular Python was automatic: import pandas and start manipulating rows. That default has changed.
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Dynamic batching: the single biggest throughput lever in model serving
A model server processing one request at a time pays fixed costs for every execution:
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Decision trees: how they split, why they overfit, and how to read one
A decision tree turns prediction into a sequence of readable questions:
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Outliers: detect, understand, and only then decide to delete
An outlier is a record that looks unusual relative to other observations. That definition says nothing about whether the record is wrong.
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Activation functions in 2026: why ReLU won and what’s replacing it
ReLU remains the cheapest dependable baseline, but modern transformer feed-forward blocks increasingly favor smooth, gated designs—especially GELU, SiLU, and SwiGLU—because they preserve a gradient pa
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Feature stores and reproducible training pipelines
A model is not reproducible merely because its training script has a fixed random seed. You must also reproduce the exact feature definitions, historical values, timestamps, dependency graph, and mode
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Rule learning: RIPPER, decision lists, and models that output human-readable rules
Most classifiers return a label or probability. A rule learner returns logic that a person can inspect and execute:
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Scaling and normalization: StandardScaler vs MinMaxScaler vs RobustScaler, and the models that don’t care
Suppose a dataset contains two useful features:
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Eigenvalues and SVD without tears: compress an image to see them work
An RGB image looks visual to us, but to NumPy it is three matrices: one each for red, green, and blue. Real images contain repeated structure—smooth gradients, correlated colors, recurring edges, and
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DuckDB: an analytics warehouse that fits in your laptop’s pocket
If you’ve ever wanted to analyze gigabytes of data without provisioning a database server or signing up for a cloud data warehouse, DuckDB is worth a serious look.