YoVDO

Bernhard Schölkopf- From Statistical to Causal Learning

Offered By: International Mathematical Union via YouTube

Tags

Causal Inference Courses Artificial Intelligence Courses

Course Description

Overview

Explore the fundamental concepts driving research in artificial intelligence systems in this 48-minute lecture by Bernhard Schölkopf. Delve into the evolution of AI approaches, from symbolic methods to statistical learning, and finally to interventional models based on causality. Examine how some of the most challenging problems in machine learning and AI are inherently linked to causality, and discover why progress in these areas may depend on advancing our understanding of causal modeling and inference from data. Access accompanying slides for a comprehensive visual aid to enhance your learning experience.

Syllabus

Bernhard Schölkopf: From statistical to causal learning


Taught by

International Mathematical Union

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Artificial Intelligence for Robotics
Stanford University via Udacity
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent