Unit 1: Understanding Reproducibility in MLOps
Unit 2: Code and Environment Versioning
Unit 3: Data Versioning with DVC
Reproducibility and Experiment Tracking for MLOps Engineers
Master the essential principles and tools for achieving reproducible ML workflows and robust experiment tracking, crucial for reliable model deployment and MLOps success.
Unit 1: Introduction to Experiment Tracking
Unit 2: MLflow for Experiment Tracking
Unit 3: Weights & Biases for Experiment Tracking