Beginner Lessons

Fireside Chat - The Future of LLMs // David Hershey & Daniel Jeffries // LLMs in Prod Con Part 2

Preemption Chaos and Optimizing Server Startup // Bradley Heilbrun // LLMs in Prod Conference Part 2

Using LLMs to Power Consumer Search at Scale // Aravind Srinivas // LLMs in Prod Conference Part 2

Enabling Defense Missions with Local LLMs // Gerred Dillon // LLMs in Production Conference Part 2

LLM XGBoost - Can a Fine-Tuned LLM Beat XGBoost on Tabular Data? // Sebastian Cattes // LLMs Part 2

Evolving AI Governance for an LLM World // Diego Oppenheimer // LLMs in Production Conference Part 2

From an API to a Chat GPT Plugin // Mathieu Bastian // LLMs in Production Conference Part 2

Everything We've Been Taught About ML is Wrong // Emmanuel Ameisen // LLMs in Prod Con Part 2

Language Models: Developing Apps - Challenges & Solutions // Barak Turovsky /MLOps Podcast #169 clip

From Experiment to Prompt Tracking in MLOps // Piotr Niedźwiedź // MLOps Podcast #168 clip

Experiment Tracking in the Age of LLMs // Piotr Niedźwiedź // MLOps Podcast #168

Making LLM Inference Affordable // Daniel Campos // LLMs in Production Conference Part 2

Benchmarking LLM performance with LangChain Auto-Evaluator // Lance Martin //LLMs in Prod Con Part 2

Challenges in Providing LLMs as a Service // Hemant Jain // LLMs in Production Conference Part 2

Lessons Learned Productionising LLMs for Stripe Support // Sophie Daly // LLMs in Prod Con Part 2

LLM on K8s // Panel 2 // LLMs in Conference in Production Conference Part 2

Transforming AI Safety & Security // Manojkumar Parmar // LLMs in Production Conference Part 2

Navigating Through the Generative AI Landscape // Azin Asgarian // LLMs in Prod Conference Part 2.

LLMs For the Rest of Us // Vikram Sreekanti & Joseph Gonzalez // LLMs in Prod Conference Part 2

Foundation Models in the Modern Data Stack // Ines Chami // LLMs in Prod Conference Part 2

Building Data and ML Products // Roy Hasson & Santona Tuli // MLOps Podcast #166 short clip 1

Eliminating Garbage In/Garbage Out for Analytics and ML // Roy Hasson & Santona Tuli // Podcast #166

It Worked When I Prompted It // Soham Chatterjee // LLMs in Production Conference Part 2

Evaluation // Panel 1 // Large Language Models in Production Conference Part 2

Evaluating LLM-based Applications // Josh Tobin // LLMs in Prod Conference Part 2

Automating ML Infrastructure // Rob Hirschfeld // MLOps Podcast #164 short clip

Build and Customize LLMs in Less than 10 Lines of YAML // Travis Addair // LLMs in Prod Con Part 2

Taking ImgFlip's 'This Meme Does Not Exist' to the Next Level with a LLM // Stefan Ojanen // LLMs

Scalable Evaluation and Serving of Open Source LLMs // Waleed Kadous // LLMs in Prod Conference

Dataframes Are All You Need: MLOps on Easy Mode // Jay Chia // MLOps Meetup #124

The Long Tail of ML Deployment // Tuhin Srivastava // MLOps Podcast #161

Fine-Tuning LLMs: Best Practices and When to Go Small // Mark Kim-Huang // MLOps Meetup #124

Using LLMs to Punch Above your Weight! // Cameron Feenstra // LLMs in Production Conference Talk

Guiding LLMs While Staying in the Driver's Seat // Jacob van Gogh // LLMs in Prod Con Lightning talk

LLM Deployment with NLP Models // Meryem Arik // LLMs in Production Conference Lightning Talk 2

Efficiently Scaling and Deploying LLMs // Hanlin Tang // LLM's in Production Conference

Building Defensible Products with LLMs // Raza Habib // LLMs in Production Conference Talk

How LlamaIndex Can Bring Power of LLM's to Your Data //Jerry Liu // LLM's In Prod Lightning talk 3

LangChain: Enabling LLMs to Use Tools // Harrison Chase // LLMs in Production Conference

DevTools for Language Models: Unlocking the Future of AI-Driven Applications // Diego Oppenheimer

Scaling Algorithms with Machine Learning: A Google Engineer's Journey

Declarative MLOps - Streamlining Model Serving on Kubernetes // Rahul Parundekar// MLOps Meetup #123

Code Modularization Techniques // Rodolfo Núñez // MLOps Podcast #153 short clip

Multilingual Programming and a Project Structure to Enable It // Rodolfo Núñez // MLOps Podcast #153

How A Manager Became a Believer in DevOps for Machine Learning // Keith Trnka // MLOps Podcast #152

Airflow Sucks for MLOps // Stephen Bailey // MLOps Podcast #141

Prioritizing Needs in ML Platform Design // Jean-Michel Daignan // MLOps Podcast #151 short clip

The Importance of Communication Skills in Customer-Facing Machine Learning Engineering