Скачать или смотреть ML unit5 in just 25 minutes| easy explanation| 100% PASS

In this video I have explained unit5 of ml in just 25 minutes
ml of btech jntuh unit5

NOTES LINK👇🔗
https://notes-theta-eight.vercel.app/

TOPICS COVERED👇
1.REINFORCEMENT LEARNING, GETTING LOST EXAMPLE
2.MARKOV CHAIN MONTE CARLO METHODS-SAMPLING,PROPOSAL DISTRIBUTION
3.MARKOV CHAIN MONTE CARLO GRAPHICAL MODELS
4.BAYESIAN NETWORKS
5.MARKOV RANDOM FIELDS
6.HIDDEN MARKOV MODELS
7.TRACKING METHODS
REINFORCEMENT LEARNING (RL)
Reinforcement Learning is a learning method in which an agent learns by interacting with an environment.
The agent:
• Observes the current state
• Takes an action
• Receives a reward (positive or negative)
• Updates its knowledge
• Repeats the process until it learns the best behavior.
RL is based on trial and error and delayed rewards.
















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