t81_558_deep_learning
Artifact_Removal_GAN
| t81_558_deep_learning | Artifact_Removal_GAN | |
|---|---|---|
| 10 | 1 | |
| 5,671 | 46 | |
| - | - | |
| 3.4 | 0.0 | |
| 7 days ago | about 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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t81_558_deep_learning
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Wednesday Daily Thread: Beginner questions
I am just getting into Machine Learning with Python. I have an M1 MacBook Air and (somehow) managed to install Tensorflow according to this tutorial https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/tensorflow-install-mac-metal-jul-2021.ipynb , which is apparently the bread and butter of machine learning.
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Install Tensorflow through Miniforge on M1 Mac
I skimmed through other forums and they suggest using Miniforge instead of Anaconda. Specifically, I was following this guide: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/tensorflow-install-mac-metal-jul-2021.ipynb
- Does anyone have Keras for image classification up and running on a Mac?
- layers.Conv2D( ) -> Running this function kills the Python Kernel
- Different Outputs on Mac M1 and Windows
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Learning Roadmap for Beginners in ML (I'm following it). What do you guys think about it?
Applications of Deep Neural Networks with Keras (2021), by Jeff Heaton https://sites.wustl.edu/jeffheaton/t81-558/ https://arxiv.org/pdf/2009.05673.pdf
- i figured out how to animate the GAN i've been training!
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D Simple Questions Thread December 20 2020
dnnlib.SubmitConfig clearly does not exist in that version of dnnlib, and looks to have never existed in the NVlabs/stylegan2-ada repository. However, it does exist in the NVlabs/stylegan2 repository. My hunch is that the code was haphazardly ported from StyleGAN2 to the newer StyleGAN2-ADA, and it is simply an oversight after porting. There is an issue in the jeffheaton/t81_558_deep_learning repository (I assume you are you eluzzi5?), so I'll add this info to that issue.
I am using the following code to try to run StyleGAN on Google Colab: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_07_3_style_gan.ipynb
Artifact_Removal_GAN
What are some alternatives?
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
Deep-Learning - In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
RefinementGAN - Official implementation of the paper: https://arxiv.org/abs/2108.04957
DotA2-Icon-GAN - Using GANs to generate DotA2 Ability Icons
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
pix2pix - This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.
handwritten-digits-recognizer-webapp - This is my first experience with machine learning
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022