# Ceyron/machine-learning-and-simulation

All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

Repository: https://github.com/Ceyron/machine-learning-and-simulation
Canonical: https://ross.abutalabs.com/products/machine-learning-and-simulation
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: education, machine-learning, simulation
Last push: 2026-05-22T06:22:43+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 83, release rhythm 8, longevity 100
- inputs: {"age_days": 2013, "days_push": 103, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1199, forks 224 (observed 2026-08-28T04:03:57.924548+00:00)

## What it is
A collection of handwritten notes and Jupyter Notebook source code accompanying a YouTube channel on machine learning and simulation. It covers math foundations, probabilistic ML, sparse matrices, continuum mechanics, and automatic differentiation.

## Use cases
- learn math foundations for machine learning
- study probabilistic machine learning and variational inference
- understand automatic differentiation and adjoints
- learn continuum mechanics for FEM and CFD
- find worked examples of probability distributions and MLE
- learn how sparse matrices are implemented in C

## When to choose
- you prefer video-based learning with accompanying code and notes
- you want mathematical depth behind ML and simulation methods
- you need free educational material spanning ML, probability, and mechanics

## When to avoid
- you need production-ready ML software or libraries
- you want a structured textbook or certification course
- you need guaranteed up-to-date coverage of the latest deep learning frameworks

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, simulation, math, data-science
- domain: machine-learning, tutorials, mathematics, simulation
- platform: python, cross-platform
- tags: jupyter-notebooks, youtube-course, probabilistic-ml, continuum-mechanics, automatic-differentiation, sparse-matrices, lecture-notes

## Member repositories
- Ceyron/machine-learning-and-simulation (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:57.924548+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 2026-08-30T06:20:51.786220+00:00, confidence not recorded.
  - readme: https://github.com/Ceyron/machine-learning-and-simulation (fetched 2026-08-28T04:03:57.924548+00:00, sha d1094d8c923e)
- Data as of 2026-08-30T08:39:29.467469+00:00.