# llSourcell/Learn_Machine_Learning_in_3_Months

This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube

Repository: https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months
Canonical: https://ross.abutalabs.com/products/learn_machine_learning_in_3_months
License Family: other
Last push: 2024-04-02T11:45:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3106, "days_push": 883, "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 7599, forks 2311 (observed 2026-08-28T04:10:01.931962+00:00)

## What it is
A curated 3-month curriculum for learning machine learning, created by Siraj Raval to accompany his YouTube video. It links to courses and videos covering math foundations, Python for data science, TensorFlow, and deep learning.

## Use cases
- learn machine learning in 3 months
- find a structured ML study curriculum
- learn the math prerequisites for machine learning
- get started with deep learning as a beginner
- find free courses and videos for self-studying ML

## When to choose
- you want a free, structured self-study path into machine learning
- you need a week-by-week plan covering math through deep learning
- you prefer learning via videos and MOOCs

## When to avoid
- you need maintained, runnable code or a software library
- you want a formal certification or instructor support
- you need up-to-date course links, as some may be outdated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, data-science
- domain: machine-learning, deep-learning, data-science, tutorials
- platform: cross-platform
- tags: curriculum, self-study, youtube, siraj-raval, math-for-ml

## Member repositories
- llSourcell/Learn_Machine_Learning_in_3_Months (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:01.931962+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 2026-08-29T17:36:51.627799+00:00, confidence not recorded.
  - readme: https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months (fetched 2026-08-28T04:10:01.931962+00:00, sha fb124a86bbe2)
- Data as of 2026-08-30T08:39:29.467469+00:00.