# reshamas/fastai_deeplearn_part1

Notes for Fastai Deep Learning Course

Repository: https://github.com/reshamas/fastai_deeplearn_part1
Canonical: https://ross.abutalabs.com/products/fastai_deeplearn_part1
Homepage: http://www.fast.ai
Language: HTML
License: MIT
License Family: permissive
Topics: deep-learning, python3, pytorch, image-recognition, python
Last push: 2025-03-07T14:08:32+00:00

## Health v2 (maintenance only)
Score: 37/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 10, release rhythm 35, longevity 100
- inputs: {"age_days": 3223, "days_push": 544, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1121, forks 306 (observed 2026-08-28T04:03:39.847761+00:00)

## What it is
A collection of study notes, course outlines, and troubleshooting guides for the fast.ai Practical Deep Learning for Coders course, maintained by Reshama Shaikh. It includes versioned course outlines, glossaries of deep learning terms, FAQs for beginners, and technical tool guides for cloud workflows.

## Use cases
- study notes for the fastai deep learning course
- troubleshooting common fastai errors
- learn deep learning with pytorch as a beginner
- set up jupyter notebook and AWS for fastai
- find fastai resources and best practices
- compare fastai course versions v1 to v3

## When to choose
- you are taking the fast.ai Practical Deep Learning course and want supplementary notes
- you are a beginner hitting common setup errors in fastai
- you need curated fastai resources, glossaries, and cloud tooling tips

## When to avoid
- you need the official fastai library or course materials themselves
- you want production deep learning code or a maintained software package
- you need notes covering the latest fastai course versions beyond v3

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, developer-tools
- domain: deep-learning, machine-learning, tutorials, education
- platform: python, cross-platform
- tags: fastai, course-notes, pytorch, study-guide, image-classification, jupyter

## Member repositories
- reshamas/fastai_deeplearn_part1 (main) score 37

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:39.847761+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 2026-08-30T06:41:01.812206+00:00, confidence not recorded.
  - readme: https://github.com/reshamas/fastai_deeplearn_part1 (fetched 2026-08-28T04:03:39.847761+00:00, sha 93c4d5a07aab)
  - homepage: http://www.fast.ai (fetched 2026-08-29T12:44:48.072852+00:00, sha 63043d372c3a)
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  - site_page: https://www.fast.ai/posts/2025-11-07-solveit-features.html (fetched 2026-08-29T12:44:48.085504+00:00, sha c9795e6a6d56)
  - site_page: https://www.fast.ai/posts/2025-02-03-cpath-foundation/index.html (fetched 2026-08-29T12:44:48.088988+00:00, sha 5f38b4d61844)
  - site_page: https://www.fast.ai/posts/2021-08-16-ai-taxonomy.html (fetched 2026-08-29T12:44:48.091493+00:00, sha 46466db16635)
  - site_page: https://www.fast.ai/posts/2021-08-17-eleven-videos.html (fetched 2026-08-29T12:44:48.093522+00:00, sha ebdf816e426f)
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  - site_page: https://www.fast.ai/posts/2020-08-21-fastai2-launch.html (fetched 2026-08-29T12:44:48.097605+00:00, sha ba6b599f5ca0)
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- Data as of 2026-08-30T08:39:29.467469+00:00.