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Overview

GitHub LinkedIn About I'm Leandro Mineti. I work at the intersection of data science, AI, and the question of how people and machines do their best thinking together.

News

Blog 2 months ago
Why you need a machine that never sleeps
A small always-on server, dark to the internet, that keeps an Obsidian vault converging and version-controlled, hosts coding agent sessions I can drive from a phone, and - unplanned - reaches my tasks, mail, and calendar.
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Blog 4 months ago
AI coding tools should reach beyond the editor
AI-assisted coding accelerates one pillar of development work - writing code. The real leverage is an assistant that works across all three pillars, project management and infrastructure included, closing the whole loop instead of one third of it.
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Blog 3 years ago
Enabling data-driven results
Integrating decision support systems into business processes - the building blocks of descriptive, predictive, and prescriptive systems, and why results happen in processes, not in the systems themselves.
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Blog 6 years ago
Artificial intelligence: a concise conceptual introduction
A conceptual map of artificial intelligence - from the definition of intelligence to the five abstraction layers of every machine learning solution.
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Blog 6 years ago
Simple linear regression
Fitting a line from scratch: the model and its assumptions, least-squares estimates derived by hand and by optimizer, the sampling distributions of the coefficients, a confidence band for the mean response, and R².
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Blog 6 years ago
Multiple linear regression
Linear regression with several features in matrix form: the closed-form least-squares estimator derived and computed, the sampling distribution of the coefficients, and a from-scratch look at LASSO, ridge, and elastic-net regularization.
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Blog 7 years ago
Single-parameter frequentist inference
Three estimators for the mean of a normal sample - sample mean, least squares, and maximum likelihood - derived from scratch and shown to coincide, then confidence intervals checked against the truth.
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Blog 7 years ago
The law of large numbers
Why the average of many trials settles on the expected value - shown with coin and dice simulations in NumPy, then the weak law stated and proved via Chebyshev's inequality.
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