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Clean Code for Data Scientists // Matt Sharp // MLOps Podcast # 160

Clean Code for Data Scientists // Matt Sharp // MLOps Podcast # 160

FromMLOps.community


Clean Code for Data Scientists // Matt Sharp // MLOps Podcast # 160

FromMLOps.community

ratings:
Length:
46 minutes
Released:
Jun 7, 2023
Format:
Podcast episode

Description

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 just started a new job at Shopify.

// MLOps Jobs board
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links


--------------- ✌️Connect With Us ✌️ -------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Catch all episodes, blogs, newsletters, and more: https://mlops.community/

Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Abi on LinkedIn: https://www.linkedin.com/in/goabiaryan/
Connect with Matt on LinkedIn: https://www.linkedin.com/in/matthewsharp/
Released:
Jun 7, 2023
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.