- Introduction
- Types of Learning
- Applications of reinforcement learning
Artificial Intelligence IV - Reinforcement Learning in Java
Quick Facts
particular | details | |||
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 449 ₹2,499
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
Introduction
Markov Decision Processes (MDP) Theory
- Markov decision processes basics I
- Markov decision processes basics II
- Markov decision processes - equations
- Markov decision processes - illustration
- Bellman-equation
- How to solve MDP problems?
- Mathematical formulation of reinforcement learning
- Reinforcement Learning Basics Quiz
Markov Decision Processes - Value Iteration
- What is value iteration?
- Value iteration implementation I
- Value iteration implementation II
- Value iteration implementation III
- Value iteration implementation IV
- Value iteration implementation V
Markov Decision Processes - Policy Iteration
- What is policy iteration?
- Value iteration vs policy iteration
Q Learning Theory
- Q learning introduction
- Q learning introduction - the algorithm
- Q learning illustration
- Mathematical formulation of Q learning
- Q Learning Quiz
Pathfinding with Q-learning
- ---- PATHFINDING ----
- Pathfinding with Q-learning I
- Pathfinding with Q-learning II
- Pathfinding with Q-learning III
- Pathfinding with Q-learning IV
- ---- SHORTEST PATH ----
- Shortest path with Q-learning
Exploration vs Exploitation Problem
- Exploration vs exploitation problem
- N-armed bandit problem introduction
- N-armed bandit problem implementation I
- N-armed bandit problem implementation II
- Applications: A/B testing in marketing
- Exploration vs. Exploitation Quiz
Deep Reinforcement Learning Theory
- What is deep Q learning?
- Deep Q learning and ε-greedy strategy
- Deep Q-learning introduction - remember and replay
- Mathematical formulation of deep Q learning
- Deep Q Learning Quiz
Course Materials (DOWNLOADS)
- Course materials
Articles
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