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Cartesian Faith

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Cartesian Faith

Category Archives: data science

Slides for “Achieving Practical Reproducibility with Transparency and Accessibility” (DSSV 2020)

July 30, 2020

I was invited to speak at the ASA’s Symposium on Data Science and Statistics as well as the SAMSI/IASC conference …

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Request for comments on planned features for futile.logger 1.5

December 15, 2018

I will be pushing a new version of futile.logger (version 1.5) to CRAN in January. This version introduces a number …

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Preview my new book: Introduction to Reproducible Science in R

November 12, 2018

I’m pleased to share Part I of my new book “Introduction to Reproducible Science in R“. The purpose of this …

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How to call bullshit on AI companies (aka a short lesson on recall)

April 10, 2018

Now that software ate the world, what’s for dessert? Those in the know know that it’s AI. It seems everyone …

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Data-driven unit testing for data scientists and quant developers alike

March 12, 2018

Often overlooked, testing is a critical process that saves time over the long term and enables building complex systems. Unit …

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Fermi Poker – Gambling for quants and data scientists

June 4, 2017

Fermi problems are well known for honing your ability to estimate quantities that are difficult (or impossible) to measure. Named …

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Modeling data with functional programming, Part I

April 14, 2017

The latest draft of my book is available. This will be my last pre-publication update, as I’m in the process …

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What you need to know about data augmentation for machine learning

October 6, 2016

Plentiful high-quality data is the key to great machine learning models. But good data doesn’t grow on trees, and that …

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A simple workflow for deep learning

September 29, 2016

As a follow-up to my Primer On Universal Function Approximation with Deep Learning, I’ve created a project on Github that …

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A primer on universal function approximation with deep learning (in Torch and R)

September 23, 2016

Arthur C. Clarke famously stated that “any sufficiently advanced technology is indistinguishable from magic.” No current technology embodies this statement …

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