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

Coursera

Optimize Vision Datasets: Augment and Analyze

Coursera via Coursera

Overview

Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
This short course teaches you how to train, validate, and improve predictive models using practical, industry-ready workflows. You’ll learn to apply supervised and unsupervised algorithms, run 5-fold cross-validation, and interpret metrics like precision, recall, and F1 to understand model reliability. Through videos, guided reflections, readings, and hands-on labs, you’ll practice building complete pipelines, engineering new features, and evaluating model improvements against performance targets. By the end of the course, you’ll be able to apply validation techniques confidently, iterate on your models using data-driven decisions, and explain performance results clearly to technical and non-technical stakeholders.

Syllabus

  • Optimize Vision Datasets: Augment and Analyze
    • This short course teaches you how to train, validate, and improve predictive models using practical, industry-ready workflows. You’ll learn to apply supervised and unsupervised algorithms, run 5-fold cross-validation, and interpret metrics like precision, recall, and F1 to understand model reliability. Through videos, guided reflections, readings, and hands-on labs, you’ll practice building complete pipelines, engineering new features, and evaluating model improvements against performance targets. By the end of the course, you’ll be able to apply validation techniques confidently, iterate on your models using data-driven decisions, and explain performance results clearly to technical and non-technical stakeholders.

Taught by

ansrsource instructors

Reviews

Start your review of Optimize Vision Datasets: Augment and Analyze

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.