
Rust and machine learning #3 with Alec Mocatta (Ep. 109)
06/22/20 • 23 min
In the 3rd episode of Rust and machine learning I speak with Alec Mocatta.
Alec is a +20 year experience professional programmer who has been spending time at the interception of distributed systems and data analytics. He's the founder of two startups in the distributed system space and author of Amadeus, an open-source framework that encourages you to write clean and reusable code that works, regardless of data scale, locally or distributed across a cluster.
Only for June 24th, LDN *Virtual* Talks June 2020 with Bippit (Alec speaking about Amadeus)
In the 3rd episode of Rust and machine learning I speak with Alec Mocatta.
Alec is a +20 year experience professional programmer who has been spending time at the interception of distributed systems and data analytics. He's the founder of two startups in the distributed system space and author of Amadeus, an open-source framework that encourages you to write clean and reusable code that works, regardless of data scale, locally or distributed across a cluster.
Only for June 24th, LDN *Virtual* Talks June 2020 with Bippit (Alec speaking about Amadeus)
Previous Episode

Rust and machine learning #2 with Luca Palmieri (Ep. 108)
In the second episode of Rust and Machine learning I am speaking with Luca Palmieri, who has been spending a large part of his career at the interception of machine learning and data engineering.
In addition, Luca contributed to several projects closer to the machine learning community using the Rust programming language. Linfa is an ambitious project that definitely deserves the attention of the data science community (and it's written in Rust, with Python bindings! How cool??!).
- Series Announcement - Zero to Production in Rust https://www.lpalmieri.com/posts/2020-05-10-announcement-zero-to-production-in-rust/
- Zero To Production #0: Foreword https://www.lpalmieri.com/posts/2020-05-24-zero-to-production-0-foreword/
- Taking ML to production with Rust: a 25x speedup https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/
Next Episode

Rust and machine learning #4: practical tools (Ep. 110)
In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly.
To make a comparison with the Python ecosystem I will cover frameworks for linear algebra (numpy), dataframes (pandas), off-the-shelf machine learning (scikit-learn), deep learning (tensorflow) and reinforcement learning (openAI).
Rust is the language of the future.
Happy coding!
- BLAS linear algebra https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
- Rust dataframe https://github.com/nevi-me/rust-dataframe
- Rustlearn https://github.com/maciejkula/rustlearn
- Rusty machine https://github.com/AtheMathmo/rusty-machine
- Tensorflow bindings https://lib.rs/crates/tensorflow
- Juice (machine learning for hackers) https://lib.rs/crates/juice
- Rust reinforcement learning https://lib.rs/crates/rsrl
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