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Kyle Gallatin

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Apr 5, 2023

Thoughts on Stateful ML, Online Learning, and Intelligent ML Model Retraining

Designing scalable architecture for online and offline continuous learning systems

Thoughts on Stateful ML, Online Learning, and Intelligent ML Model Retraining

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Kyle Gallatin

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Jul 28, 2022

Everything I Hate About Machine Learning

I recently gave a talk about Machine Learning in Production, and had a really great time making this slide:

Everything I Hate About Machine Learning

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Jul 29, 2022

Components of a Production ML System Using Only Python

A foundational base to learn—and build on—the basics of MLOps components

Components of a Production ML System Using Only Python

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Sep 17, 2019

The Rise of the Term “MLOps”

Properly Operationalized Machine Learning is the New Holy Grail

The Rise of the Term “MLOps”

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Jun 9, 2023

Training a Machine Learning Model on a Kafka Stream

Updating a machine learning model online and in near real-time using training data generated by a Kafka producer

Training a Machine Learning Model on a Kafka Stream

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Dec 23, 2022

Building a lil’ Stateful, ML Application for Online Learning

Checkout the code here. For prose, keep reading…

Building a lil’ Stateful, ML Application for Online Learning

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AWS in Plain English

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Kyle Gallatin

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Nov 11, 2021

Machine Learning at the AWS re:Invent Conference 2021

5 production-grade Machine Learning talks in the re:Invent conference of 2021 that I’m excited about.

Machine Learning at the AWS re:Invent Conference 2021

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Aug 7, 2021

Kubernetes Practical Intro for Data Scientists

Yup, it’s yet another “intro to k8s” article. The world didn’t need it, you didn’t ask for it, and yet I already had it in a gist somewhere

Kubernetes Practical Intro for Data Scientists

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Jul 17, 2021

5 Different Ways to Deploy your Machine Learning Model with AWS

On the pros and cons of different approaches to getting your model out into the world.

5 Different Ways to Deploy your Machine Learning Model with AWS

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Mar 2, 2021

The Fastest Way to Deploy Your ML App on AWS with Zero Best Practices

You’ve been working on your ML app and a live demo is coming up fast. You wanted to push it to Github, add Docker, and refactor the code…

The Fastest Way to Deploy Your ML App on AWS with Zero Best Practices

Kyle Gallatin

Kyle Gallatin

Software Engineer for ML Infra. Building scalable, operationalized machine learning services. I don’t represent my employer.

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