MLOps Tutorial #1: Intro to Continuous Integration for ML MLOps Tutorial #2: When data is too big for Git MLOps Tutorial #3: Track ML models with Git & GitHub Actions MLOps Tutorial #4: GitHub Actions with your own GPUs MLOps Tutorial #5: Automated Testing for Machine Learning MLOps Tutorial #6: Behavioral tests for models with GitHub Actions MLOps Chat: How Should We Test ML Models? with Data Scientist Jeremy Jordan MLOps Tutorial #7: GitHub Actions with R for Data Science (put a ggplot in your pull request!) Using DVC Experiments in Transfer Learning GitOps for ML - How to convert machine learning notebooks to reproducible DVC pipelines Best MLOps Practices for Building End-to-End Machine Learning Computer Vision Projects with Alex Kim Machine Learning Experiment Tracking with VS Code, Git, and DVC Transforming a Jupyter Notebook into a Reproducible Pipeline for ML Experiments How to Turn Your IDE into a Machine Learning Experimentation Platform with the DVC ext for VS Code Applying GitOps Principles at Every Step of an E2E MLOps Project - A Workshop