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

YouTube

Why Synthetic Data is Needed for AI Fairness and Explainability

Data Science Conference via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore machine learning techniques for audio data modeling in this 47-minute conference talk from Data Science Conference Europe 2022, where speakers Paul Tiwald and Alin Kalam delve into audio source separation applications. Gain insights into the importance of synthetic data for achieving AI fairness and explainability through detailed technical discussions presented at the in-person event in Belgrade.

Syllabus

Why Synthetic Data is needed for AI Fairness and Explainability | P.Tiwald&A.Kalam | DSC Europe 2022

Taught by

Data Science Conference

Reviews

Start your review of Why Synthetic Data is Needed for AI Fairness and Explainability

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.