AAIF Live

Data Mesh - Data Quality Control Mechanism for MLOps? // Scott Hirleman // MLOps Coffee Sessions #77

MLOps Song

Build a Culture of ML Testing and Model Quality // Mohamed Elgendy // MLOps Coffee Sessions #76

Towards Observability for ML Pipelines // Shreya Shankar // MLOps Coffee Sessions #75

Scaling Biotech // Jesse Johnson // MLOps Coffee Sessions #74

Federated Learning: Machine Learning on the Edge // Varun Kumar Khare // Reading group #3

Just Build It! Tips for Making ML Engineering and MLOps Real // Andy McMahon // MLOps Meetup #91

On Structuring an ML Platform 1 Pizza Team //Breno Costa & Matheus Frata //MLOps Coffee Sessions #73

Neoway's approach to MLOps is explored, emphasizing the critical role of team structure and communication. Breno Costa and Matheus Frata from Neoway detail how they redesigned their teams based on the "team-first approach" and concepts from the book "Team Topologies" to align with desired software architectures. This i...

2021 MLOps Year in Review // Vishnu Rachakonda and Demetrios Brinkmann // MLOps Coffee Sessions #72

Setting up an ML Platform on GCP: Lessons Learned // Mefta Sadat // MLOps #71

2022 Predictions for MLOps and the Industry // Reah Miyara // MLOps Coffee Sessions #70

Building 12-Factor Data Apps with Kedro // Ivan Danov // MLOps Meetup #90

Building for Small Data Science Teams // James Lamb // MLOps Coffee Sessions #69

Modern ML Stack is a Lie

ML Drift - How to Identify Issues Before They Become Problems // Amy Hodler // MLOps Meetup #89

Wikimedia MLOps // Chris Albon // MLOps Coffee Sessions #68

The ML Test Score // Skylar Payne // MLOps Reading Group #2

ML Stepping Stones: Challenges & Opportunities for Companies // John Crousse // Coffee Sessions #67

Machine Learning at Reasonable Scale // Jacopo Tagliabue // MLOps Coffee Sessions #66

The Not So Talked About Reasons Model Monitoring Fails // Oren Razon // MLOps Meetup #88