# ashishpatel26/Andrew-NG-Notes

This is Andrew NG Coursera Handwritten Notes.

Repository: https://github.com/ashishpatel26/Andrew-NG-Notes
Canonical: https://ross.abutalabs.com/products/andrew-ng-notes
Language: Jupyter Notebook
License Family: other
Topics: andrewng, andrew-ng, andrew-ng-course, andrew-ng-machine-learning, deep-learning, neural-network, deep-neural-networks, reinforcement-learning, machine-learning, pandas, numpy, ml, dl, coursera, coursera-machine-learning, data-science, python, pytorch, neural-networks
Last push: 2025-08-01T12:17:07+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 34, release rhythm 35, longevity 100
- inputs: {"age_days": 2643, "days_push": 397, "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 3797, forks 1267 (observed 2026-08-28T04:08:19.990012+00:00)

## What it is
A collection of handwritten and markdown notes covering Andrew Ng's Coursera Machine Learning and Deep Learning Specialization courses, compiled into PDFs and per-course articles. It also links to lecture playlists and includes Jupyter notebooks from the courses.

## Use cases
- find handwritten notes for Andrew Ng's machine learning course
- review deep learning specialization concepts quickly before an exam
- get a single PDF summary of all five deep learning courses
- supplement Coursera lectures with condensed study notes
- learn neural networks, CNNs, and sequence models from course notes
- access machine learning course notebooks and lecture links in one place

## When to choose
- you are taking or reviewing Andrew Ng's Coursera ML or Deep Learning Specialization
- you prefer handwritten or condensed notes over rewatching lectures
- you want a quick reference covering neural networks, CNNs, and sequence models

## When to avoid
- you need production machine learning code or a software library
- you want a complete textbook with exercises and graded assignments
- you need notes for topics beyond Andrew Ng's course syllabus

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, nlp
- domain: machine-learning, deep-learning, data-science, tutorials
- platform: cross-platform
- tags: handwritten-notes, coursera, andrew-ng, study-notes, neural-networks

## Member repositories
- ashishpatel26/Andrew-NG-Notes (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:19.990012+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 2026-08-29T18:26:55.566566+00:00, confidence not recorded.
  - readme: https://github.com/ashishpatel26/Andrew-NG-Notes (fetched 2026-08-28T04:08:19.990012+00:00, sha ec680456e7aa)
- Data as of 2026-08-30T08:39:29.467469+00:00.