Course description
Reinforcement Learning
In this course, you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in uncertain environment.
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Who should attend?
Required Pre-requisites
- Fundamentals in AI & ML, Probability, Python, Neural Networks, Frameworks, Deep Learning library like PyTorch/ Theano/ TensorFlow
Edureka offers you complimentary self-paced courses
- Statistics and Machine learning algorithms
- Python Essentials
Certification / Credits
Towards the end of the course, Edureka certifies you as a "Reinforcemnt Learning Professional" based on the project you submit.
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