CS231n-2017 and stanford-cs231n-assignments-2020
These are competitors—both provide complete assignment solutions for CS231n, just from different course iterations (2017 vs 2020), so a learner would choose one based on which semester's materials they're following.
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.
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.
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