Deep & Reinforcement Learning (CS702 (B))-Computer Science and Engineering (VII-Semester) | RGPV

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• Syllabus

• Syllabus - Deep & Reinforcement Learning (CS702 (B))

• Unit 1

• Introduction to Deep Learning
• Gradient Descent Variants
• Recurrent Neural Networks

• Unit 2

• Autoencoders
• Regularization Techniques

• Unit 3

• Advanced Techniques in Deep Learning
• Convolutional Neural Networks
• Recent Trends in Deep Learning Architectures

• Unit 4

• Introduction to Reinforcement Learning
• Dynamic Programming in RL
• Function Approximation and Least Squares Methods

• Unit 5

• Advanced Q-learning and Policy Gradient
• Hierarchical RL and POMDPs
• Actor-Critic Method and Inverse Reinforcement Learning
• Recent Trends in RL Architectures