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A New Era of Creativity: Expert-in-the-loop Generative AI at Stitch Fix

How Stitch Fix uses an expert-in-the-loop approach with generative AI to drive innovation.

Polymorphic, Recursive Interfaces Using Go Generics

Go's generics solve a previously-unsolvable problem with interfaces, but awkwardly

2022 Intern Projects

A sampling of the projects and areas of research done by our 2022 interns.

Leveraging the Plain Old Python Function

How Stitch Fix enables data scientists to do more, by doing less.

Client Time Series Model: a Multi-Target Recommender System based on Temporally-Masked Encoders

A Multi-Target Recommender System that is a significant improvement for both the quality of our recommendations and the maintainability of our systems

Algo Hour - Large Scale Data & ML Monitoring with whylogs | Alessya Visnjic

Algo Hour, Oct 11th, 2022 - Featuring Alessya Visnjic from whyLogs!

Experts in-the-Loop at Stitch Fix

Our stylists' expertise is a differentiator for Stitch Fix. Here is how we take that expertise into account when designing algorithmic systems.

Gotchas in Jetpack Compose Recomposition

Understanding recomposition in Jetpack Compose is critical to optimizing application performance. Here are some "gotchas" to avoid.

Configuration Driven Machine Learning Pipelines

How configuration driven Machine learning pipelines help streamline the model development at Stitch Fix.

Validating your data with Hamilton

In late 2021 we released Hamilton, Stitch Fix’s open-source microframework for managing dataflows. With feedback from the community, we’ve implemented an exciting new feature -- the ability to validate the data hamilton generates! In this post we detail the new capabilities and talk a little bit about next steps.