Building an MLOps Platform with MLflow for Rapid Model Productionalization
Offered By: Databricks via YouTube
Course Description
Overview
Explore the challenges and solutions of productionalizing machine learning models in this 30-minute conference talk from Databricks. Learn how DataSentics built a dedicated MLOps platform centered around MLflow to streamline the model deployment process. Discover their approach to addressing common issues in MLOps, including team communication, environment differences, and data management. Gain insights into real-life experiences that shaped the platform's development and see a live demo of model deployment. Understand the key design principles aimed at reducing productionalization time to mere minutes. Delve into lessons learned and future steps for improving the MLOps workflow.
Syllabus
Introduction
Data Science is a Silver Bullet
Motivation
Mission
Template
Demo
Create Project
Running Experiments
Training
Conclusion
Taught by
Databricks
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent