# merveenoyan/my_notes

My small cheatsheets for data science, ML, computer science and more.

Repository: https://github.com/merveenoyan/my_notes
Canonical: https://ross.abutalabs.com/products/my_notes
License: Apache-2.0
License Family: permissive
Last push: 2023-02-02T19:52:13+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 94
- inputs: {"age_days": 1320, "days_push": 1308, "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 1649, forks 116 (observed 2026-08-28T04:05:16.750014+00:00)

## What it is
A collection of handwritten graduate-school lecture notes and cheatsheets covering data science, machine learning, statistics, deep learning, image processing, and data structures & algorithms. Notes are compiled into PDFs and hosted on GitHub with a mirrored dataset on Hugging Face.

## Use cases
- study for machine learning exams
- review statistics cheatsheets before an interview
- brush up on deep learning concepts quickly
- find image processing study notes
- revise data structures and algorithms for job interviews
- get quick reference cheatsheets for data science topics
- learn Hugging Face basics from cheatsheets

## When to choose
- you want concise cheatsheets to review topics you've already studied
- you're preparing for exams or technical interviews in ML, DL, or CS fundamentals
- you prefer handwritten, visual study notes

## When to avoid
- you need a comprehensive tutorial that teaches topics from scratch
- you want polished, typeset documentation rather than handwritten notes
- you need up-to-date, actively maintained course material

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, data-science, machine-learning, deep-learning, image-processing
- domain: data-science, machine-learning, deep-learning, computer-vision, education, tutorials
- platform: cross-platform
- tags: cheatsheets, lecture-notes, study-notes, statistics, data-structures, algorithms, handwritten-notes, interview-prep

## Member repositories
- merveenoyan/my_notes (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:16.750014+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 2026-08-30T03:45:10.110136+00:00, confidence not recorded.
  - readme: https://github.com/merveenoyan/my_notes (fetched 2026-08-28T04:05:16.750014+00:00, sha fb5f7b1550aa)
- Data as of 2026-08-30T08:39:29.467469+00:00.