Advanced Lessons

Vector Databases and Large Language Models // Samuel Partee // LLMs in Production Conference

ML Evolution & Recurring Themes // Waleed Kadous // MLOps Podcast # 155 short clip

Improving User Experience with YouChat Conversational Interface

The Trade-off between Lookup Efficiency and Accuracy in LLMs

Evaluating Language Model Outputs: Beyond Grammar and Coherence

The Evolution of Foundation Models and the Complexity of Automation

Balancing the Benefits and Risks of Language Models

The Challenges of Productionizing Machine Learning in the Era of Big Models

The Importance of Domain Experts in Creating Stress Tests

AI and the Future of Database Optimization // Alex Debrie // MLOps Podcast #146 short clip

Decision Making in Design Engineering // Murtuza Shergadwala // MLOps Podcast #142 clip

Balancing Technical Expertise and Motivation in ML Interviews

Applying Machine Learning to DNA Storage and Decoding // Luis Ceze // MLOps Podcast Shorts

Bringing DevOps Agility to ML // Luis Ceze // Coffee Sessions #121

Turning Redis into a Composable, ML Data Platform // Samuel Partee // Coffee Sessions #111

FLOps with Scaleout's Open-core Platform // Marco Capuccini // MLOps Meetup #104

Don't Listen Unless You Are Going to Do ML in Production // Kyle Morris // MLOps Coffee Sessions #87

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

Model Monitoring: The Million Dollar Problem // Loka Team // MLOps Meetup #87

Reliable Machine Learning // Niall Murphy // Coffee Sessions #54 short clip

Federated Learning / Distributed Learning // Sahbi Chaieb // Coffee #51 short clip

ML Security: Why should you care? // Sahbi Chaieb // MLOps Coffee Sessions #51

Model serving platform // Kyle Gallatin // Coffee #43 short clip

DataOps Manifesto - DataOps is Data Management Reborn // Chris Bergh // MLOps Meetup #64 short clip

CI/CD for MLOPS Definition // Monmayuri Ray // MLOps Coffee Sessions #41 short clip

Underspecification Paper Key Takeaways // D. Sculley // MLOps Clips

The Godfather Of MLOps // D. Sculley // MLOps Coffee Sessions #32

What’s changed in the MLOps ecosystem? Explained by the Godfather of MLOps // Coffee Session Clip

How Explainable AI is Critical to Building Responsible AI // Krishna Gade // MLOps Meetup #53

MLOps Meetup #21 // Deep Dive on Paperspace Tooling // Misha Kutsovsky

Model monitoring with Fury Data Apps at Mercado Libre

ML platform Fury Data Apps at Mecado Libre

What parts of the mercado libre ML platforms are automatted

Litox View of the state of ML today

Fury Platform and Fury Data Apps at Mercado Libre

MLOps community meetup #11 // Machine Learning at Scale in Mercado Libre with Carlos de la Torre

Training ML models on live datasets in a GDPR world

ML tooling in large companies

MLOps Problems in different size companies

Friction Between Data Scientists and Software Engineers

How Phil Winder got into Data Science and Software Engineering

MLOps and Monitoring

Building an MLOps Team? Key ideas to keep in mind

Automatically Retrain Machine Learning Models? Are best practices worth it?

Explainability, Black boxes and EU white paper on reproducibility