Hands-on Pytorch
This repository provides tutorial code for deep learning researchers to learn PyTorch. If you have any questions in this document, please contact me: hoesungryu@korea.ac.kr
Course Objectives
This is an introductory basic-level course on Machine Learning and Deep Learning with Pytorch. This course who are interested in not only understanding the basic methodology of deep learning & data analytics but also play around with coding yourself.
Syllabus
| Event Type | Date | Topic |
|---|---|---|
| 1 | July 26 | Environment setting and python basic |
| 2 | July 27 | Pytorch basic |
| 3 | July 28 | Linear Regression |
| 4 | July 29 | Classification |
| 5 | July 30 | Know-how: Model training |
| 6 | July 31 | MLP (Multi-Layer Perceptrone |
| 7 | Aug 03 | CNN (Convolution Neural Network) |
| 8 | Aug 04 | RNN (Recurrent neural Network) |
| 9 | Aug 05 | RL (Reincement Learning) |
| 10 | Aug 06 | Mini_Kaggle: Facial Expression Recognition on AffectNet |
| 11 | Aug 10 | Awards and Closing |
Reference
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