MLOps Platforms From Zero - Databricks, MLFlow-MLRun-SKLearn
Dive into a comprehensive 2.5-hour video tutorial on building MLOps platforms using Databricks, AutoML, SKLearn, and AWS. Learn to start an MLOps project, set up CI/CD, and invoke ML library code. Explore end-to-end MLOps with Databricks to AWS containers, spin up Databricks clusters, and transition from Pandas to Spark. Create a fake news classifier using Kaggle and AutoML, register models, and set up inference endpoints. Utilize Github CodeSpaces and FastAPI to serve MLFlow models with Swagger documentation. Discover Iguazio's feature store capabilities and leverage AWS Cloud9 for developing containerized ML models. Finally, deploy your containerized model using AWS App Runner. Access source code and additional resources for further learning in cloud computing, data engineering, and MLOps.