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Solving MLOps from First Principles - A Framework for Effective Tool Selection

Offered By: Open Data Science via YouTube

Tags

MLOps Courses Artificial Intelligence Courses Data Science Courses Machine Learning Courses Data Engineering Courses Open Source Courses

Course Description

Overview

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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.

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

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