stanford-cs231n-assignments-2020 and cs231n-convolutional-neural-networks-solutions
These are competitors, as both repositories provide assignment solutions for the CS231n course, with each offering a set of solutions from a different year and potentially different deep learning framework approaches.
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.
About cs231n-convolutional-neural-networks-solutions
madalinabuzau/cs231n-convolutional-neural-networks-solutions
Assignment solutions for the CS231n course taught by Stanford on visual recognition. Spring 2017 solutions are for both deep learning frameworks: TensorFlow and PyTorch.
This provides completed assignments for the Stanford CS231n course on visual recognition, helping students learn to build and train convolutional neural networks. You get structured problem sets and their solutions, which demonstrate how to implement deep learning models using TensorFlow and PyTorch. This is ideal for students or self-learners taking the CS231n course or similar deep learning programs.
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