Python Tutorial (Deep Learning course, 2 Sessions)
Please note that this session will be given in Japanese.
Overview
This program aims to foster a "third place" for the computational science community by providing opportunities for interaction among users from academia and industry, with a particular focus on users of our center. Therefore, participation is open not only to users of the center, but also to those affiliated with academic institutions and private companies that use our facilities, as well as individuals from other academic institutions and private organizations who:
• Are interested in simulations and computational science
• Have been interested in supercomputing but have never used a supercomputer, or have only recently started using one
• Are interested in programming (Python programming)
All such individuals are welcome to participate.
Python Tutorial (Deep Learning course)
This tutorial is organized with the cooperation of the Advanced High-Performance Computing Infrastructure Systems Research Division (Professor Date) of our center and will be developed and taught by graduate students affiliated with the division. Drawing on their own experiences, the tutorial is designed for those who would like to start learning Python, as well as those who have tried it before but gave up and would like to make another attempt. Participants are encouraged to ask questions freely in a relaxed environment.
Note: Google Colaboratory will be used as the primary IDE (Integrated Development Environment) during the seminar. Google Colaboratory is free to use, but a Google account is required. For more information about Google Colaboratory, please refer to this page. Participants are also welcome to use any Python-supported IDE they are familiar with and ask questions accordingly.
Program
The Python Tutorial (Deep Learning course) consists of two sessions held over two consecutive weeks.
Day 1: Fundamentals of Deep Learning
| Friday, October 30, 2:00 PM - 4:00 PM | |
|---|---|
| 14:00 - 15:45 | Tutorial: Fundamentals of Deep Learning Through an introduction to the basic concepts of deep learning and hands-on exercises in tabular data classification, participants will learn the complete workflow from data preparation to training and validation. (Instructor: Ryusei Kadowaki, Advanced High-Performance Computing Infrastructure Systems Research Division, D3 Center / Graduate School of Information Science and Technology, The University of Osaka) |
| 15:45 - 16:00 | Wrap-up and Q&A Session |
Day 2: Applications of Deep Learning
| Friday, November 6, 2:00 PM - 4:00 PM | |
|---|---|
| 14:00 - 14:10 | Opening Remarks Susumu Date, Professor, Advanced High-Performance Computing Infrastructure Systems Research Division, D3 Center, The University of Osaka |
| 14:10 - 15:45 | Tutorial: Applications of Deep Learning Through advanced deep learning topics (including image data classification), participants will learn techniques for model improvement and application design. (Instructor: Ryusei Kadowaki, Advanced High-Performance Computing Infrastructure Systems Research Division, D3 Center / Graduate School of Information Science and Technology, The University of Osaka) |
| 15:45 - 16:00 | Wrap-up and Q&A Session |
Important Notes for Participation
This event will be conducted online. Please ensure that you have access to a stable internet connection. Details regarding how to join will be provided separately.
Date : October 30, 14:00 - 16:00
November 6, 14:00 - 16:00
Instructor: D3 Center
Venue: Online
Type : Lecture, Hands-on
Quota: 15(Hands-on), 100(listen only)
Application deadline: October 23
