📕[ML Study]

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

📝Study Curriculum

There might be some adjustments

1. Python basic, Numpy, Matplotlib
2. Introduction (Introduction of artificial intelligence, history of development, NLP practical use example, CV practical use example)
3. ML Theory -> Pytorch Basic - MLP
4. CNN(AlexNet/VGGNet/GoogleNet/ResNet) - RNN(basic, seq2seq)
5. NLP - text classification (bag of worlds, CNN, embedding, Bert?)
6. OpenCV, YOLO -> (Also provides Raspberry training materials)
7. SOTA Model Practice
8. A week of projects

📅Week's Homework

Organize this week's homework

📑Study Reference

paperswithcode