Machine Learning Zoomcamp: A Free Course on ML Engineering (15k stars)
What it does
All text below is quoted directly from the project README.
>Learn ML engineering for free in 4 months! Register here
Who Should Join:
- Already have programming experience and want to move into machine learning engineering.
- Want a structured introduction to machine learning without assuming prior ML knowledge.
- Want to understand both model development and production deployment.
- Learn best by completing homework and building end-to-end projects.
- Want portfolio projects that demonstrate practical machine learning skills.
- Benefit from cohort deadlines, community support, peer review, and certificate eligibility.
>Frame the problem, prepare the data, train and evaluate the model, expose it through an API, package it, and deploy it.
Repository
DataTalksClub/machine-learning-zoomcamp
Repository stats
|Metric|Value|
|:-|:-|
|Stars|14,862|
|Forks|3.3k|
|Last release|dl-models (2025-08-15)|
|Languages|Jupyter Notebook 97.7%, Python 1.8%, Other 0.5%|
|Contributors|136|
|AI contributor accounts (Claude / Codex / Cursor / Copilot)|@Copilot (2 commits)|
|AI co-authored commits|Copilot: 2|
Main contributor
|Field|Value|
|:-|:-|
|Name|Alexey Grigorev|
|GitHub|@alexeygrigorev|
|Commits to this repo|1,323 (top contributor)|
|Bio|Running @DataTalksClub and hacking some personal projects|
|Company / Location|Berlin, Germany|
|Followers|6.3k|
──────────────────────────────
📌 How many great GitHub repos have you discovered and completely forgotten about?
Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week.
📬 Never lose track of great repos again. Subscribe free.
3 points
Mentions
Machine Learning Zoomcamp: A Free Course on ML Engineering (15k stars) What it does All text below is quoted directly from the project README. >Learn ML engineering for free in 4 months! Register here Who Should Join: - Already have programming experience and want to move into machine learning engineering. - Want a structured introduction to machine learning without assuming prior ML knowledge. - Want to understand both model development and production deployment. - Learn best by completing homework and building end-to-end projects. - Want portfolio projects that demonstrate practical machine learning skills. - Benefit from cohort deadlines, community support, peer review, and certificate eligibility. >Frame the problem, prepare the data, train and evaluate the model, expose it through an API, package it, and deploy it. Repository DataTalksClub/machine-learning-zoomcamp Repository stats |Metric|Value| |:-|:-| |Stars|14,862| |Forks|3.3k| |Last release|dl-models (2025-08-15)| |Languages|Jupyter Notebook 97.7%, Python 1.8%, Other 0.5%| |Contributors|136| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|@Copilot (2 commits)| |AI co-authored commits|Copilot: 2| Main contributor |Field|Value| |:-|:-| |Name|Alexey Grigorev| |GitHub|@alexeygrigorev| |Commits to this repo|1,323 (top contributor)| |Bio|Running @DataTalksClub and hacking some personal projects| |Company / Location|Berlin, Germany| |Followers|6.3k| ────────────────────────────── 📌 How many great GitHub repos have you discovered and completely forgotten about? Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week. 📬 Never lose track of great repos again. Subscribe free.
🔹 5-Fold Cross-Validation: Evaluated model stability using KFold 📌 Notebook (Homework): github.com/wapratama/ml-zc2026/blob/main/homework… 📷 Course: DataTalksClub/machine-learning-zoomcamp ➡ Next step → Module 5: Deployment! #MLZoomcamp #machinelearning #datascience #scikitlearn > @DataTalksClub
That comparison comes from Module 4 of Machine Learning Zoomcamp. The lesson walks through it step by step, with code: github.com/DataTalksClub/machine-learning-zoomcam…
In Homework 4, you evaluate models on the 2026 lead-scoring dataset. The deadline is October 20, 2026 at 01:00 CEST (October 19 at 23:00 UTC). The Module 4 lessons, videos, and code are on GitHub: github.com/DataTalksClub/machine-learning-zoomcam… 3/3