Managing Experiments, LLMs, and Model Serving with MLflow

In this webinar, MLflow Ambassador and Machine Learning Engineer Thor Steen Larsen from DSB demonstrates how to move beyond messy local files to a structured, enterprise-ready machine learning environment using MLflow. Thor explains how MLflow provided essential tools for experiment tracking, model evaluation, and various deployment strategies suitable for both Data Scientists and ML Engineers. Topics Covered: 🔹 Getting Started with MLflow 🔹 MLflow for AI & GenAI 🔹 Deployment Strategies 🔹 MLOps Environments 🔹 Algorithmic Prompt Optimization 🔹 Deploying to production with MLflow and DABs 🔹 New & Upcoming Features 🔹 Tracking Image Datasets with MLflow 🗣️ Hosted by Pål de Vibe, Databricks MVP 💻 Monthly Euro Databricks Community Slack Hangout