Dive into a comprehensive 42-minute talk by Dean Pleban that addresses the challenges of MLOps and provides a framework for selecting the right tools for data teams. Learn how to overcome "MLOps Fatigue" by applying first principles thinking to analyze problems and choose optimal solutions. Explore practical examples and guidelines focused on open-source tools to streamline workflows in machine learning, data science, and AI. Gain insights into defining problems, evaluating solutions, and integrating tools effectively. Perfect for professionals in data engineering, machine learning training, and natural language processing looking to make informed decisions about their MLOps stack.
Solving MLOps from First Principles - A Framework for Effective Tool Selection
Overview
Syllabus
- Intro
- About the speaker
- Frist Principles Thinking
- 4 Stages of Grief
- Assumptions about the SOLUTION
- Step 1 Define the Problem
- Step 2 Define the problem parameters
- Step 3 - Google the problem
- Step 4 - Evaluate solutions
- Step 5 - Integrate
- Questions
Taught by
Open Data Science
