tils (page 6)
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Curse of Dimensionality
Why high-dimensional data quickly becomes sparse, distances stop making sense, and ML algorithms struggle
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When to Use PowerTransformer vs StandardScaler
A concise comparison of StandardScaler and PowerTransformer, their purposes, effects, and when to choose each in a Python ML pipeline.
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Difference Between Bayesian Credible Intervals and Frequentist Confidence Intervals
A practical comparison of Bayesian credible intervals versus frequentist confidence intervals and how to interpret them.
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Dot Product's Role in Similarity, Projections, and Gradients
Exploring how the dot product's measure of vector alignment underpins similarity metrics, projections, and gradients in ML and calculus
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Why sharing GPU power between AI servers and personal PCs doesn't really work
A practical look at why latency, hardware variety, and security issues make distributed GPU computing impractical