Half day Tutorial at ADCOM 2024
Date: Friday, December 20, 2024 Time: 9:00AM – 1:00PM
Title:
Learn to Design and Implement Deep Reinforcement Learning Solutions with MATLAB
This hands-on tutorial will equip you with the skills to tackle complex AI problems using deep reinforcement learning techniques. You’ll learn how to:
- Formulate Reinforcement Learning Problems: Understand the key components of a reinforcement learning problem, including states, actions, rewards, and policies.
- Leverage MATLAB’s Deep Learning Toolbox: Utilize MATLAB’s powerful tools to design and train deep neural networks for reinforcement learning.
- Train Agents Interactively: Use MATLAB’s interactive environment to train agents in real-time and visualize their learning process.
- Apply Reinforcement Learning to Real-World Scenarios: Explore applications of reinforcement learning in autonomous systems, robotics, and other domains.
Who Should Attend:
- Researchers and engineers interested in AI and machine learning
- Students and practitioners seeking to learn reinforcement learning techniques
- Individuals working in robotics, autonomous systems, or game development
- Anyone interested in AI and Machine Learning
This is a Hands-On tutorial and as such, participants will need to have access to a laptop with internet connection.
Limited Seats Available! Don’t miss this opportunity to gain practical experience in deep reinforcement learning. Register now to secure your spot.
TUTOR PROFILE
Dr. Souvick Chatterjee
Senior Team Lead- Principal Customer Success Engineer: MathWorks, IN- Bangalore
Souvick leads the Education Team in MathWorks in southern part of India and is based out of Bangalore. He manages strategic academic collaborations in research and education with universities/institutions. He is recipient of Best PhD Thesis Award and Young Scientist Award from International Society for Energy, Environment and Sustainability. He worked in University of Illinois at Chicago as postdoctoral associate and at EnterpriseWorks Chicago as strategy consultant for commercialization of academic innovations. He has co-authored multiple journal articles, book chapters, and is co-inventor of two patents. Souvick has a BE in Mechanical Engineering and a MS-PhD dual degree from Virginia Tech and Jadavpur University on Biomedical Engineering.
Dr. Souvick Chatterjee
MathWorks
