Technical Workshop Series - Machine Learning and Neural Networks using PyTorch (2nd Offering) by: Soroush Ziaeinejad

Tuesday, July 23, 2024 - 15:00

Technical Workshop Series

Machine Learning and Neural Networks using PyTorch (2nd  Offering)

Presenter:  Soroush Ziaeinejad

Date: Tuesday, July 23rd, 2024

Time: 3:00 pm

Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)

 

This is a hands-on workshop, please bring your laptop.

 

Abstract: 

This workshop provides an overview of a significant framework in deep learning: PyTorch (and PyTorch Geometric.) The first session covers PyTorch, addressing its core concepts, architecture design, and model optimization processes. The second session introduces PyTorch Geometric, focusing on the application of graph neural networks in analyzing complex graph data. Participants will engage with practical examples and theoretical discussions, enhancing their understanding of these frameworks' roles in advancing deep learning research. This workshop is aimed at researchers and students seeking to deepen their knowledge of deep learning technologies.
 

Workshop Outline:

  • Introduction to PyTorch: Understanding the core concepts and its dynamic computation graph.
  • Tensors and Operations: Basics of tensor operations, which are fundamental to neural networks.
  • Building Blocks of Neural Networks: Detailed exploration of layers, activation functions, and loss functions.
  • Training Neural Networks: A step-by-step guide to training models, including backpropagation, optimization, and regularization techniques.
  • Practical Application: Implement a simple neural network to solve a classification or regression problem, illustrating the workflow from data preparation to model evaluation.

 

Prerequisites:

  • Basic programming experience in Python.
  • Understanding of fundamental machine learning concepts.
  • Familiarity with the core principles of neural networks is helpful but not mandatory.

 

Biography: 

Soroush is a Ph.D. student and research assistant at the School of Computer Science. His main research area is Natural Language Processing and Information Retrieval on social networks.

 

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.