CS231n and computer-vision

These are competitors—both are independent student solution repositories for the same Stanford CS231n course assignments, offering alternative implementations that serve the same educational purpose.

CS231n
43
Emerging
computer-vision
43
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Stars: 490
Forks: 185
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 506
Forks: 246
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 computer-vision

khanhnamle1994/computer-vision

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

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.

visual recognition image classification deep learning neural networks machine learning engineering

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