- What is MLOps
- MLOps maturity model
- Running example: NY Taxi trips dataset
- Why do we need MLOps
- Course overview
- Experiment tracking intro
- Getting started with MLflow
- Experiment tracking with MLflow
- Run hyperparameter tuning using Hyperopt, and then logging all the run results in MLflow
- Saving and loading models with MLflow
- Promoting best model to Model registry
- Filter out some of the best performing models on validation sets, run them through test set, thereby promoting the best model to model registry
- Workflow orchestration
- Prefect 2.0
- Concept of task and flow
- Work-queues and agents
- Previewing work-queues and view scheduled runs
- IntervalSchedule vs CronSchedule
- Created a mini project that downloaded, ingested, trained and validated on datasets automatically based on a scheduled interval time period.
- Creating a new virtual environment
- Create a script for prediction
- Put script into Flask app
- Dockerize the app
credits: DataTalksCub
author: chekwei