cs231n VS deep-learning-v2-pytorch

Compare cs231n vs deep-learning-v2-pytorch and see what are their differences.

cs231n

Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition (by mirzaim)
Deep Learning cs231n cs231n-assignment Notes Computer Vision Solutions Pytorch stanford cs231 spring-2021 2021 Machine Learning convolutional-neural-networks neural-network
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deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101 (by udacity)
Deep Learning neural-network convolutional-networks Pytorch recurrent-networks style-transfer sentiment-analysis
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cs231n deep-learning-v2-pytorch
1 1
42 5,176
- 0.5%
0.0 0.0
over 2 years ago 10 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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cs231n

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deep-learning-v2-pytorch

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What are some alternatives?

When comparing cs231n and deep-learning-v2-pytorch you can also consider the following projects:

coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

stable-diffusion-reference-only - img2img version of stable diffusion. Anime Character Remix. Line Art Automatic Coloring. Style Transfer.

stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford

torchdyn - A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

monodepth2 - [ICCV 2019] Monocular depth estimation from a single image

stanford-CS229 - Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng [UnavailableForLegalReasons - Repository access blocked]

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

glasses - High-quality Neural Networks for Computer Vision 😎

DeepLearning - Contains all my works, references for deep learning

gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

cs231n vs coursera-deep-learning-specialization deep-learning-v2-pytorch vs stable-diffusion-reference-only cs231n vs stanford-cs229 deep-learning-v2-pytorch vs torchdyn cs231n vs Deep-Learning-Computer-Vision deep-learning-v2-pytorch vs monodepth2 cs231n vs stanford-CS229 deep-learning-v2-pytorch vs hyperlearn cs231n vs monodepth2 deep-learning-v2-pytorch vs glasses cs231n vs DeepLearning deep-learning-v2-pytorch vs gan-vae-pretrained-pytorch