CS231n-2017 and CS231n

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

CS231n-2017
43
Emerging
CS231n
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: 606
Forks: 186
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 490
Forks: 185
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-2017

Burton2000/CS231n-2017

Completed the CS231n 2017 spring assignments from Stanford university

This repository contains completed assignments from Stanford University's CS231n 2017 course on Convolutional Neural Networks for Visual Recognition. It provides practical solutions and code examples for deep learning tasks using Python, PyTorch, and TensorFlow. Aspiring machine learning engineers or students seeking to learn and practice deep learning concepts will find this useful.

deep-learning-education computer-vision-training neural-network-practice machine-learning-student pytorch-tensorflow-examples

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

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