Summary

Keywords

6-s897-machine-learning-for-healthcare-spring-2019 attention map desiderata falling rule lists interpretable models leafage lime sampling trust

Full Transcript

MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: https://ocw.mit.edu/6-S897S19 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j Prof. Szolovits discusses interpretability because modern machine learning models are very difficult to understand. He discusses different methods that have been used to attempt to overcome inscrutable models. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu

Continue this lesson in the app

Install CourseHive on Android or iOS to keep learning while you move.

Related Courses

Direção de Arte no Cinema e Jogos: Fundamentos Essenciais

Transforme sua criatividade em carreira: descubra os segredos da Direção de Arte no cinema, jogos e design gráfico com especialistas e aprenda a criar mundos visuais incríveis. Inscreva-se agora e revolucione sua visão artística!

⭐ 4.0

29 ratings

0 min

30-Day Beginner Guitar Challenge for New Players

Master the Guitar in 30 Days: Your Ultimate Beginner Challenge! Unleash your inner guitarist with step-by-step lessons designed to transform you from novice to confident player. Join Your Guitar Academy and kickstart your musical journey today!

⭐ 4.3

36 ratings

7 hours