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Deep Reinforcement Learning For Research (A-Z in Bangla- Recorded)

Course Description

Master deep reinforcement learning techniques with our comprehensive course. Dive into cutting-edge algorithms, hands-on exercises, and real-world applications. Elevate your understanding of AI and robotics while optimizing your career prospects. Enroll now and unlock the potential of deep reinforcement learning!

Reinforcement Learning

  • Introduction
  • Application of Reinforcement Learning
  • Core Components of RL
  • Agent
  • State
  • Environment
  • Next State
  • Reward
  • Q-Table
  • Q-Learning
  • Bellman Equation

Deep Reinforcement Learning

  • Q-Learning
  • Deep Q-network (DQN)
  • Policy Gradient Methods
  • Actor-Critic Methods
  • Deep Deterministic Policy Gradient (DDPG)
  • Twin Delayed DDPG (TD3)

Deep Reinforcement Learning For Research

  • How to Select Topic
  • How to Find out Research Idea from the Literature Review
  • How to Make a Idea Proposal
  • Implement one or two Deep RL Algorithm to Our Proposed Idea
  • Result Comparison

Evaluation

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Tasfiq Kamran

Aminul Mahi

Shaiful Islam

MD Asadullah Shibli

Obaydullah Hasib

Nirban Mitra Joy

Md Maniruzzaman Manir

Md Anower Hossain

Mehedi Azad

Alomghir Hossain

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Key Topics:

  • Core Components of RL
  • Q-Table, and Q-Learning
  • Deep Q-network (DQN)

Price

3000

Discount Price

1800

Duration

2 Months

Available Seats

75

Class Type

Pre-Recorded

Access

Lifetime

Time

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