khanhnamle1994/computer-vision

Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition

43
/ 100
Emerging

This resource provides a comprehensive learning path for understanding and implementing visual recognition systems using deep learning. You'll gain practical skills in setting up, training, and fine-tuning neural networks for tasks like image classification. This is ideal for aspiring machine learning engineers, data scientists, or researchers who want to build sophisticated computer vision applications.

506 stars. No commits in the last 6 months.

Use this if you are an aspiring machine learning engineer or data scientist who wants to learn how to build and debug advanced computer vision models from the ground up.

Not ideal if you are looking for a pre-built tool or library to simply apply computer vision models without understanding their underlying mechanisms.

visual recognition image classification deep learning neural networks machine learning engineering
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 25 / 25

How are scores calculated?

Stars

506

Forks

246

Language

Jupyter Notebook

License

Last pushed

Feb 08, 2018

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/khanhnamle1994/computer-vision"

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