Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

How Implementing Machine Learning Ended Up with an If-Else - Lessons from OpenShift Cluster Prediction

DevConf via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a DevConf.CZ 2023 conference talk that delves into the challenges and pivotal decisions in Machine Learning projects. Learn from Juan Díaz and Katya Gordeeva's experiences in extracting value from OpenShift cluster data, including their project on predicting upgrade issues. Gain insights on maintaining focus on business goals, defining success metrics early, and choosing appropriate technologies. Discover the importance of stakeholder communication, addressing moral challenges, and overcoming qualification and scalability issues in ML implementations. Understand why 85% of ML projects fail and how to avoid common pitfalls through practical lessons learned in a real-world scenario.

Syllabus

Intro
Agenda
Context
Problem Statement
Typical Problem
Data Set
Moral Challenges
AI ML
Metric choice
Prediction
False positives
Fscore
Baseline
Iterating
Issues
Theories
Qualification challenges
Scalability
Questions

Taught by

DevConf

Reviews

Start your review of How Implementing Machine Learning Ended Up with an If-Else - Lessons from OpenShift Cluster Prediction

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.