14. Causal Inference, Part 1
MIT 6.S897 Machine Learning for Healthcare, Spring 2019
Instructor: David Sontag
View the complete course: https://ocw.mit.edu/6-S897S19
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j
Prof. Sontag discusses causal inference, examples of causal questions, and how these guide treatment decisions. He explains the Rubin-Neyman causal model as a potential outcome framework.
License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Видео 14. Causal Inference, Part 1 канала MIT OpenCourseWare
Instructor: David Sontag
View the complete course: https://ocw.mit.edu/6-S897S19
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j
Prof. Sontag discusses causal inference, examples of causal questions, and how these guide treatment decisions. He explains the Rubin-Neyman causal model as a potential outcome framework.
License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Видео 14. Causal Inference, Part 1 канала MIT OpenCourseWare
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
What is causal inference, and why should data scientists know? by Ludvig Hult
15. Causal Inference, Part 2
Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56
Statistical vs. Causal Inference: Causal Inference Bootcamp
Yoshua Bengio Guest Talk - Towards Causal Representation Learning
Why start using uplift models for more efficient marketing campaigns
Causal Inference Methods for Real-World Evidence
Solving Heterogeneous Estimating Equations Using Forest Based Algorithms
Keynote: Judea Pearl - The New Science of Cause and Effect
What is Causation? | Episode 1511 | Closer To Truth
Inferring the effect of an event using CausalImpact by Kay Brodersen
1.3 - Correlation Does Not Imply Causation and Why
Counterfactuals: Causal Inference Bootcamp
Causal Inference in Data Science From Prediction to Causation by Amit Sharma | DataEngConf NYC '16
16. Reinforcement Learning, Part 1
A.I. teaches itself to drive in Trackmania
Lectures on Causality: Jonas Peters, Part 1
Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability)
Causal Inference: Making the Right Intervention | QuantumBlack
How Do We Learn What Works? A Two-Step Algorithm for Causal Inference from Observational Data