Technical Workshop Series
Introduction to Neural Networks for Deep Learning (1st Offering)
Presenter: Xiaofeng Liu (Michael)
Date: Thursday, July 11th,2024
Time: 10:00 AM
Location: 4th Floor at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
Abstract:
Reinforcement learning (RL) is training machine learning models to make a sequence of decisions. Q-learning is a type of RL with a model-free environment which achieves learning by interaction with the environment instead of transition probabilities. However, Q-learning has its limitations on state and action space. This workshop will introduce the principle of neural networks and deep learning/deep Q-learning, which help solve more complicated problems.
Workshop Outline:
- What is deep learning?
- Basic of Neural Networks.
- Neural Network Architecture
- How NNs learn?
- Training DNN
- What is Deep Q-learning?
- Q&A
Prerequisites:
Principles of RL.
Biography:
Xiaofeng is a PhD Candidate in Computer Science. His research interests mainly focus on Congestion Control for V2V communication in VANET (Vehicular Ad hoc Network).
MAC STUDENTS ONLY - Register here
Reminder: Workshops marked as 1st Offering and 2nd Offering mean the exact same workshop is running at two different times - DO NOT REGISTER FOR BOTH. Students will not get points for attending the same workshop twice.