Rust is eating the world

Get ready to a faster-better-safer data science experience

When the going gets tough, the tough get going.
Thinking about performance? Squeezing your code to the last available register of the latest CPU?
It’s time for you to be serious about the Rust programming language.

How does this amazing language play with machine learning and data science?

Let me tell you about the top four episodes specifically about Rust and data science.

Is Rust flexible enough for a flexible data model? (Ep. 137)

In this podcast I get inspired by Paul Done‘s presentation about The Six Principles for Building Robust Yet Flexible Shared Data Applications, and show how powerful of a language Rust is while still maintaining the flexibility of less strict languages.

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Pandas vs Rust (Ep. 144)

Pandas is the de-facto standard for data loading and manipulation. Python is the de-facto programming language for such operations. Rust is the underdog. Or is it?
In this episode I am showing you why that is no longer the case.

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Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)

Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine.
Andy explains some challenges while he was designing the Arrow and Ballista memory models and he describes some amazing solutions.

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Polars: the fastest dataframe crate in Rust (Ep. 146)

In this episode I speak with Ritchie Vink, the author of Polars, a crate that is the fastest dataframe library at date of speaking 🙂 If you want to participate to an amazing Rust open source project, this is your change to collaborate to the official repository in the references.

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