CS231n and stanford-cs231n-assignments-2020

These are competitors—both are independent solution repositories for the same Stanford CS231n course assignments, and users would typically choose one or the other as a reference for understanding the coursework.

CS231n
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Emerging
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 23/25
Stars: 490
Forks: 185
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 178
Forks: 68
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
No License Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About CS231n

jariasf/CS231n

My assignment solutions for CS231n - Convolutional Neural Networks for Visual Recognition

This collection provides solved assignments for a university course on Convolutional Neural Networks (CNNs) for visual recognition. It offers practical examples of image classification, feature extraction, and neural network implementation. Students learning about deep learning and computer vision would use these solutions to understand core concepts and check their own work.

deep-learning-education computer-vision-study neural-networks-assignments image-recognition-learning student-resources

About stanford-cs231n-assignments-2020

amanchadha/stanford-cs231n-assignments-2020

This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).

This collection of assignments helps you learn to build AI systems that can 'see' and interpret images, similar to how human brains process visual information. You'll work with images and develop models that can classify objects, understand visual styles, or even generate new images. This is ideal for students or engineers new to computer vision and deep learning who want to build foundational skills.

image classification neural network development style transfer generative AI deep learning education

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