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. #ml #mlunit5 #mlunit5jntuh #mlunit5jntuhr22 #mlunit5jntuhr18 #machinelearning #machinelearningjntuh #machinelearningunit5 #machinelearningunit2jntuhr22 #machinelearningunitwiseexplanation #mlplaylist #mljntuhplaylist #btech #btechexams #jntuh #jntuhexams #jntuhr22 #howtopassml #troublefree #btechviponedaybatting #sandeeptalks