# virginiakm1988/ML2022-Spring

**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring

Repository: https://github.com/virginiakm1988/ML2022-Spring
Canonical: https://ross.abutalabs.com/products/ml2022-spring
Homepage: https://speech.ee.ntu.edu.tw/~hylee/ml/2022-spring.php
Language: Jupyter Notebook
License Family: other
Topics: machine-learning, deep-learning
Last push: 2022-10-18T08:57:31+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1655, "days_push": 1415, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2588, forks 539 (observed 2026-08-28T04:07:02.789994+00:00)

## What it is
Official repository of code, slides, and videos for Hung-yi Lee's Machine Learning 2022 Spring course at National Taiwan University, containing 15 homework assignments in Jupyter Notebooks. It covers topics from regression and CNNs to Transformers, GANs, BERT, and reinforcement learning.

## Use cases
- learn machine learning from a university course
- find homework exercises for deep learning
- study transformer and self-attention implementations
- learn GANs and autoencoders with code examples
- practice PyTorch with guided tutorials
- self-study a full ML curriculum
- understand BERT and self-supervised learning

## When to choose
- you want a structured, full-semester ML course with graded-style homework
- you prefer learning through Jupyter notebooks with accompanying lecture videos and slides
- you want free, official course materials covering both classic ML and modern deep learning topics

## When to avoid
- you need a production-ready ML library or framework
- you want actively updated content for the latest models
- you need a license permitting redistribution of the materials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning, tutorials
- platform: python, cross-platform
- tags: course-materials, jupyter-notebooks, hung-yi-lee, ntu, homework, pytorch, transformers, gan, reinforcement-learning, self-supervised-learning

## Member repositories
- virginiakm1988/ML2022-Spring (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:02.789994+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:22:24.588033+00:00, confidence not recorded.
  - readme: https://github.com/virginiakm1988/ML2022-Spring (fetched 2026-08-28T04:07:02.789994+00:00, sha 3de9b405565d)
  - homepage: https://speech.ee.ntu.edu.tw/~hylee/ml/2022-spring.php (fetched 2026-08-29T10:04:43.046143+00:00, sha 6c79921c4e72)
- Data as of 2026-08-30T08:39:29.467469+00:00.