marcosbenicio/ML-zoomcamp

Homeworks and notes from the Machine Learning Zoomcamp course

28
/ 100
Experimental

This collection of Jupyter notebooks provides practical implementations and mathematical foundations for various machine learning algorithms. It guides users through creating models for tasks like car price prediction, customer churn forecasting, and identifying diabetes risk factors. Data scientists, machine learning engineers, and analysts looking to deepen their understanding and build real-world models would find this valuable.

No commits in the last 6 months.

Use this if you are a data scientist or machine learning practitioner looking for hands-on examples and theoretical explanations for common ML tasks, from model building to deployment.

Not ideal if you are looking for a plug-and-play solution for a specific business problem without needing to understand the underlying machine learning concepts.

predictive-modeling data-science-education model-deployment classification-analysis regression-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 15 / 25

How are scores calculated?

Stars

10

Forks

4

Language

HTML

License

Last pushed

Feb 03, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/marcosbenicio/ML-zoomcamp"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.