Intermediate Lessons

Create a Contextual Chatbot with LLM a Vector Database in 10 Minutes // Raahul Dutta // LLMs Part 2

Treating Prompt Engineering More Like Code // Maxime Beauchemin // MLOps Podcast #167

Stopping Hallucinations From Hurting Your LLMs // Atindriyo Sanyal // LLMs in Prod Conference Part 2

Building and Curating Datasets for RLHF and LLM Fine-tuning // Daniel Vila Suero // LLMs in Prod Con

Beyond the Hype: Monitoring LLMs in Production // Claire Longo // LLMs in Prod Conference Part 2

Building Production Copilots // Tristan Zajonc // LLMs in Prod Conference Part 2

Embeddings and Retrieval for LLMs: Techniques and Challenges // Anton Troynikov // LLMs in Prod Con

Open Source and Fast Decision Making // Rob Hirschfeld // MLOps Podcast #164

Pitfalls and Best Practices — 5 lessons from LLMs in Production // Raza Habib // LLMs in Prod Con 2

Using Vector Databases: Practical Advice for Production // Sam Partee // LLMs in Prod Conference

LLMs as Intelligent Assistants // Sarah Aerni // LLMs in Prod Conference Part 2

Building LLM Applications for Production // Chip Huyen // LLMs in Prod Conference

The Emerging Toolkit for Reliable, High-quality LLM Applications // Matei Zaharia //LLMs in Prod Con

From Arduinos to LLMs: Exploring the Spectrum of ML // Soham Chatterjee // MLOps Podcast #162

Shopify's GPT Integration

LLMs in Production Conference - Part II

Bridging the Gap: MLOps Transformations in Streamlining Model Deployment

Balancing Data Sharing Concerns: Code as the Bridge

Assessing ML Test Scores: Surveys, Interviews, and Documentation Analysis

Expanding Capabilities and Ethical Considerations of AI Models

Nurturing Effective Search Skills for Engineers in PyTorch

Importance of Clean Code // Matt Sharp // MLOps Podcast #160 short clip

Clean Code for Data Scientists // Matt Sharp // MLOps Podcast # 160

LLMs in Production Conference Part 2

Addressing the Cold Start Problem: Heuristic Models and Training Data in Slack

Assessing and Improving MLOps Maturity // Maria Vechtomova & Basak Eskili // MLOps Podcast #159 clip

Privacy and Security in Slack: Safeguarding Data in Features and Models

Why is MLOps Hard in an Enterprise? // Maria Vechtomova & Basak Eskili // MLOps Podcast #159

Reasoning Machines // Justin Uberti & Jon Turow // LLMs in Production Conference Lightning Talk 1

Ensuring Accuracy and Quality in LLM-driven Products // Adam Nolte // LLMs in Prod Conference

Emerging Patterns for LLMs in Production // Willem Pienaar // LLMs in Prod Conference Lightning Talk

No Rose Without a Thorn - Obstacles to Successful LLM Deployments // Tanmay Chopra // LLMs in Prod

Value of External Resources for Building a Company Platform

Exploring Generative AI and ChatGPT for Uber's Machine Learning Platform

Unleashing Speech Intelligence through DSLMs // Andrew Seagraves // LLMs in Prod Con Lightning Talk

LangChain Apps to Production with LangChain-serve // Deepankar Mahapatro // LLMs Con Lightning talk

The Significance of Data and Balancing Inputs for Effective Model Training

Data-Centric AI: Unlocking the Power of Quality Data

Balancing Productivity & Prevention of Harmful Content Generation // Nils Reimers //Podcast 158 clip

Cohere Large Language Model at Scale // Nils Reimers // MLOps Podcast #158

Data Privacy and Security // LLMs in Production Conference Panel Discussion

The Future of Closed API Models in the Age of Open Source

Agentic Relationship Management // Ashe Magalhaes // LLMs in Production Conference Lightning Talk

Automating Task-specific Model Application with Snorkel Flow

ML Integration Challenges // Aaron Maurer & Katrina Ni // MLOps Podcast # 157

Tools and Technologies for Machine Learning in Kubernetes Environment

MLOps Build or Buy, Startup vs. Enterprise? // Aaron Maurer & Katrina Ni // MLOps Podcast # 157

Democratization of Technology through Machine Learning and Containerization