In preparation for next year's Google Solution Challenge, we propose a practice-oriented attribute curriculum.
- Period: From early October to early January (However, the midterm/final exam period will be suspended for 2 weeks)
- Practice-oriented rather than mathematics and deep theory
- Provide the materials you need to proceed
There might be some adjustments
- Python basic, Numpy, Matplotlib
- Introduction (Introduction of artificial intelligence, history of development, NLP practical use example, CV practical use example)
- ML Theory -> Pytorch Basic - MLP
- CNN(AlexNet/VGGNet/GoogleNet/ResNet) - RNN(basic, seq2seq)
- NLP - text classification (bag of worlds, CNN, embedding, Bert?)
- OpenCV, YOLO -> (Also provides Raspberry training materials)
- SOTA Model Practice
- A week of projects
Organize this week's homework