CS231n-2017 and CS231n

These are **competitors** — both are independent solution repositories for the same CS231n course assignments, just from different years (2017 vs 2016), so users would choose one based on which course iteration they're following.

CS231n-2017
43
Emerging
CS231n
42
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 17/25
Stars: 606
Forks: 186
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 72
Forks: 13
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No License Stale 6m No Package No Dependents
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

zlpure/CS231n

My Solution to Assignments of CS231n in Winter2016

This project provides solutions to assignments from the CS231n course, focusing on implementing and debugging neural networks for visual recognition. It takes raw image datasets like CIFAR-10 and outputs trained models and insights into various machine learning algorithms. Students and aspiring machine learning engineers can use this to deepen their understanding of computer vision and neural network architectures.

deep-learning-education computer-vision-training neural-network-implementation machine-learning-assignments image-classification-study

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