# deeplearningzerotoall/PyTorch

Deep Learning Zero to All - Pytorch

Repository: https://github.com/deeplearningzerotoall/PyTorch
Canonical: https://ross.abutalabs.com/products/deeplearningzerotoall-pytorch
Language: Jupyter Notebook
License Family: other
Topics: pytorch, tutorial
Last push: 2020-11-22T13:36:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2914, "days_push": 2110, "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 1396, forks 1371 (observed 2026-08-28T04:04:36.691035+00:00)

## What it is
A Korean-language educational course ('Deep Learning Zero to All Season 2') with Jupyter Notebook labs, slides, and YouTube videos teaching deep learning with PyTorch. It covers tensor manipulation, regression, classification, MLPs, CNNs, and RNNs through hands-on lab code.

## Use cases
- learn pytorch from scratch
- deep learning tutorial with jupyter notebooks
- understand linear regression and softmax in pytorch
- study cnn and resnet examples
- learn rnn and seq2seq basics
- beginner deep learning course with videos

## When to choose
- you want a structured, video-backed introduction to deep learning with PyTorch
- you prefer learning through runnable Jupyter notebook labs
- you want coverage from basic tensors through CNNs and RNNs

## When to avoid
- you need production-ready deep learning code
- you require up-to-date PyTorch APIs (code targets PyTorch 1.0.0)
- you need an officially licensed or actively updated resource

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python, cross-platform
- tags: pytorch, tutorial, jupyter-notebook, korean, video-course, neural-networks, cnn, rnn

## Member repositories
- deeplearningzerotoall/PyTorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:36.691035+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 2026-08-30T04:39:19.081246+00:00, confidence not recorded.
  - readme: https://github.com/deeplearningzerotoall/PyTorch (fetched 2026-08-28T04:04:36.691035+00:00, sha 6dba6ec94d89)
- Data as of 2026-08-30T08:39:29.467469+00:00.