May 1 · 20 min read · When a borrower takes out a personal loan, they might repay every penny, default entirely, or land anywhere in between. The interesting variable is the fraction eventually recovered: a number between
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Apr 29 · 18 min read · Every subscription business lives or dies by churn. Whether it is a B2B SaaS platform tracking annual contracts or a consumer app watching monthly renewals, the question is the same: how long will thi
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Apr 26 · 14 min read · A multi-line insurer writes auto, home, commercial property, and a dozen other policy types under one roof. Some lines see thousands of claims a year; others might see 50. Every actuary faces the same
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Apr 13 · 14 min read · You've trained a machine learning model and want to tune its hyperparameters. Each evaluation takes hours. You've tested 6 configurations so far. Where should you try next? If you read our hyperparame
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Apr 1 · 12 min read · Imagine you're a politician touring a chain of islands. Each island has a different population, and you want to spend time on each island in proportion to its population — more time on crowded islands
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Mar 29 · 16 min read · In the MLE tutorial, we estimated a coin's bias by finding the single parameter value that maximises the likelihood. Flip a coin 3 times, get 3 heads, and MLE says \(\hat{\theta} = 1.0\) — the coin al
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Feb 15 · 1 min read · What if a personality test could learn from each answer and skip the irrelevant questions? That is what we built with SoulTrace. Why Traditional Tests Fail Most personality assessments ask the same 100+ questions to everyone. Whether you are clearly ...
Join discussionNov 8, 2024 · 10 min read · TL;DR Some metrics are an average of the binary variable (0/1, False/True) — conversion rate, churn rate, etc. These metrics might not represent the actual value when there is a small sample size beneath them (one web session with one conversion lea...
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