MLOps Platforms From Zero - Databricks, MLFlow-MLRun-SKLearn
Offered By: Pragmatic AI Labs via YouTube
Course Description
Overview
Syllabus
Intro
Starting an MLOps project
Setup CI/CD
Invoke ML Library Code
End to End MLOps with Databricks to AWS Containers Diagram
Spinning up Databricks Cluster
Doing Pandas to Spark
Creating Fake News Classifier using Kaggle and AutoML
Creating Databricks AutoML Experiment
Viewing Databricks AutoML Experiment notebook
Registering models with Databricks
Setting up Inference endpoint with the Databricks platform
Using Github CodeSpaces to serve out downloaded Databricks model with MLFlow
Using FastAPI to serve Swagger documentation of MLFlow model
Feature Store Capabilities of Iguazio
Using AWS Cloud9 to develop containerized ML Models
Using AWS App Runner to serve out containerized model
Taught by
Pragmatic AI Labs
Related Courses
Implementar un modelo de aprendizaje automático con FastAPICoursera Project Network via Coursera Build A TodoList with Python, FastAPI and Vue JS
Udemy Build A TodoList with Python, FastAPI and React
Udemy Build A TodoList with Python, FastAPI and Angular
Udemy Web Applications and Command-Line Tools for Data Engineering
Duke University via Coursera