Data Science #32

Data Science #32

In this issue: a tutorial on testing percentiles; a primer on algorithmic differentiation; a search engine in 80 lines of Python; patterns and anti-patterns of data analysis reuse; how to beat proprietary LLMs with smaller open weight models; causal machine learning for predicting treatment outcomes; and more.

The sponsor of this issue is Galileo.

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Ashraf Alsadiq

Senior IT Solution Architect leading the development & delivery of comprehensive digital business solutions

2 天前

Can't wait to read Andriy Burkov

回复

Andriy Burkov, that lineup's packed. Testing percentiles and causal ML sounds like some rich material to dive into.

Ibrahim Errbibi

Business Owner @ DigitalPrompting | AI automation, digital marketing

2 天前

Sounds like you covered a lot of ground. Which topic are folks most intrigued by?

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Karla Yackuelene Pariona Romero

Hiring geniuses looking for a new career ??

2 天前

Sounds like an exciting edition filled with valuable insights. ??

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