Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction
Professor Emma Brunskill, Stanford University
https://stanford.io/3eJW8yT
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs234/index.html
Видео Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction канала stanfordonline
https://stanford.io/3eJW8yT
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs234/index.html
Видео Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction канала stanfordonline
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 2 - Given a Model of the World
An introduction to Reinforcement Learning
Lecture 7: Markov Decision Processes - Value Iteration | Stanford CS221: AI (Autumn 2019)
![2021 DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]](https://i.ytimg.com/vi/TCCjZe0y4Qc/default.jpg)
2021 DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]
“Learning to Code is Not Just for Coders” | Ali Partovi | TEDxSausalito
MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
DeepMind's Richard Sutton - The Long-term of AI & Temporal-Difference Learning
Building a Movie Recommendation Engine | Machine Learning Projects
MIT 6.S191 (2020): Reinforcement Learning
MIT Introduction to Deep Learning | 6.S191
MIT 6.S191: Reinforcement Learning
Learning and Memory: How it Works and When it Fails
Lecture 2: Machine Learning 1 - Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019)
Lecture 1 - Stanford CS229: Machine Learning - Andrew Ng (Autumn 2018)
Q Learning Intro/Table - Reinforcement Learning p.1
MIT 6.S191 (2019): Deep Reinforcement Learning
Deep Reinforcement Learning: Neural Networks for Learning Control Laws
Lecture 5: Search 1 - Dynamic Programming, Uniform Cost Search | Stanford CS221: AI (Autumn 2019)