# Iallen520/lhy_DL_Hw

Repository: https://github.com/Iallen520/lhy_DL_Hw
Canonical: https://ross.abutalabs.com/products/lhy_dl_hw
Language: Jupyter Notebook
License Family: other
Last push: 2020-03-29T08:01:51+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": 2368, "days_push": 2348, "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 1308, forks 556 (observed 2026-08-28T04:04:19.290153+00:00)

## What it is
A collection of example solutions and assignment instructions for the 2020 deep learning course by Professor Hung-yi Lee (李宏毅), written as Jupyter Notebooks. It serves as a study reference for students working through the course's homework assignments.

## Use cases
- find reference solutions for Hung-yi Lee 2020 deep learning homework
- learn deep learning by working through course assignments
- see example PyTorch implementations of course tasks
- download course assignment datasets
- study deep learning coursework in Chinese

## When to choose
- you are taking Hung-yi Lee's 2020 deep learning course and want reference solutions
- you learn best from worked homework examples in Jupyter Notebooks
- you prefer Chinese-language course materials

## When to avoid
- you need a production deep-learning library or framework
- you want actively maintained code with a license and recent updates
- you need comprehensive tutorials rather than assignment solutions

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, developer-tools
- domain: deep-learning, machine-learning, education, tutorials
- platform: python
- tags: homework, hung-yi-lee, course-assignments, jupyter-notebook, chinese, example-solutions

## Member repositories
- Iallen520/lhy_DL_Hw (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:19.290153+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 2026-08-30T04:50:03.335678+00:00, confidence not recorded.
  - readme: https://github.com/Iallen520/lhy_DL_Hw (fetched 2026-08-28T04:04:19.290153+00:00, sha 8166ea4ca87d)
- Data as of 2026-08-30T08:39:29.467469+00:00.