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zenburnmyface

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news.ycombinator.com 9mo ago

Automatic documentation screenshots (with bounding-boxes) via codex

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1pts0
pioreactor.com 3y ago

Pioreactor – The Raspberry Pi of Bioreactors

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14pts0
twitter.com 7y ago

2018 Python Packages Survey

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3pts0
python-packages-survey.com 7y ago

2018 Python Packages Survey

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1pts0
dataorigami.net 11y ago

MapReduce Joins, implemented in PySpark

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4pts0
dataorigami.net 11y ago

The Class Imbalance Problem in A/B Testing

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2pts0
www.dataorigami.net 12y ago

8 great data blogs to follow

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www.dataorigami.net 12y ago

FiveThirtyEight plot styles in Python

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2pts0
www.dataorigami.net 12y ago

The Future of Data

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www.dataorigami.net 12y ago

ShowHN: Data Origami Screencasts – level up your data science skills

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1pts1
github.com 12y ago

MIT License edit: you must return feedback to the authors

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2pts0
camdp.com 12y ago

Deriving formulas for the expected sample size needed in A/B tests

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27pts3
github.com 12y ago

Survival Regression in Python

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3pts0
blog.yhathq.com 12y ago

The right and wrong ways to estimate SaaS user lifetimes

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camdp.com 13y ago

NSA Honeypot

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www.camdp.com 13y ago

Machine Learning Counterexamples Pt.1

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camdp.com 13y ago

Machine Learning Counterexamples

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github.com 13y ago

Probabilistic Programming and Bayesian Methods for Hackers

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camdp.com 13y ago

How to win the Showdown on the Price is Right

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3pts0

meh. I feel this is just a linguistic shortcut, similar to how _trained_ biologists can talk about a species or organism evolving some trait. Of course the organism isn't _really_ evolving with any goal in mind, but that's clear to the speaker and audience. Whether or not LLMs understand (very unlikely), it's clear what we mean by an LLM "understanding": has the context + prior training to make reasonable predictions. But no one wants to write that each time.

Short answer: Yes.

Long answer: Here's an analogy. Computers have been abstracted enough that I have no idea how a compiler works, what assembly is, or what the difference between a Flash Drive and a SSD is, but I can still code as I please. Is this practice wrong? No, and I don't need to know (nor do I want to). This book tries to abstract inference (read: programming), from mathematics (read: compilers, assembly etc.).

Hi, Author here. I don't have any plans to write that blog post, but I'll can provide some resources:

1. http://timsalimans.com/observing-dark-worlds/ 2. http://timsalimans.com/winning-the-dont-overfit-competition/

You mention: "trained in mathematical Bayesian Inference in an Econometrics class but I never did anything practical with it" . This book tries to bridge that, from theory to practice. The examples I provide tend to be very practical.