Decision Making and Reinforcement Learning
Completed by 广辉 闵
January 24, 2024
47 hours (approximately)
广辉 闵's account is verified. Coursera certifies their successful completion of Decision Making and Reinforcement Learning
What you will learn
Map between qualitative preferences and appropriate quantitative utilities.
Model non-associative and associative sequential decision problems with multi-armed bandit problems and Markov decision processes respectively
Implement dynamic programming algorithms to find optimal policies
Implement basic reinforcement learning algorithms using Monte Carlo and temporal difference methods
Skills you will gain
- Category: Deep Learning
- Category: Reinforcement Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Machine Learning Methods
- Category: Machine Learning
- Category: Algorithms
- Category: Machine Learning Algorithms
- Category: Decision Intelligence
- Category: Analysis
- Category: Statistical Methods
- Category: Markov Model
