stanford-cs231 and CS231n-2017

stanford-cs231
50
Established
CS231n-2017
43
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Stars: 263
Forks: 117
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 606
Forks: 186
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About stanford-cs231

machinelearningnanodegree/stanford-cs231

Resources for students in the Udacity's Machine Learning Engineer Nanodegree to work through Stanford's Convolutional Neural Networks for Visual Recognition course (CS231n).

This project provides a curated set of resources to help you learn about Convolutional Neural Networks for visual recognition. It brings together course materials like lectures, assignments, and notes from Stanford's CS231n, along with supplementary blogs and articles. It's for students enrolled in Udacity's Machine Learning Engineer Nanodegree or anyone looking to deepen their understanding of how computers 'see' and interpret images.

machine-learning-education computer-vision deep-learning neural-networks academic-study

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

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