MLOps Coffee Sessions #160 with Matt Sharp, Data Developer at Shopify, Clean Code for Data Scientists, co-hosted by Abi Aryan.

// Abstract

Let's delve into Shopify's real-time serving platform, Merlin, which enables features like recommender systems, inbox classification, and fraud detection. Matt shares his insights on clean coding and the new book he is writing about LLMs in production.

// Bio

Matt is a Chemical Engineer turned Data scientist turned Data Engineer. Self-described "Recovering Data Scientist", Matt got tired of all the inefficiencies he faced as a Data Scientist and made the switch to Data Engineering. At Matt's last job, he ended up building the entire MLOps platform from scratch for a fintech startup called MX. Matt gives tips to data scientists on LinkedIn on how to level up their careers and has started to be known for my clean code tips in particular. Matt recently started a new job at Shopify.

// MLOps Jobs board

jobs.mlops.community

// MLOps Swag/Merch

https://mlops-community.myshopify.com/

// Related Links

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

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Connect with Matt on LinkedIn: https://www.linkedin.com/in/matthewsharp/

Timestamps:

[00:00] Matt's preferred drink

[00:54] Takeaways

[03:04] Watch out for Matt's LLMs in Production book coming up!

[03:29] Please like, share, subscribe, and join the upcoming LLMs in Production Conference Part 2!

[05:07] Raising awareness about the fundamental problems of writing clean code

[07:57] Definition of clean code[09:46] Communicable clean code

[13:52] Getting out of Jupyter notebooks at the end of their life

[17:21] Exploratory data analysis

[21:22] Most popular post on LinkedIn

[26:41] Zilliz Ad

[27:44] Best practices on production-level software engineering

[29:41] Merlin

[33:51] Upcoming Shopify projects

[39:10] Matt's upcoming LLMs in Production book

[45:06] LLMs in Production book Early Access

[46:00] Wrap up