Artifact_Removal_GAN
t81_558_deep_learning
| Artifact_Removal_GAN | t81_558_deep_learning | |
|---|---|---|
| 1 | 10 | |
| 46 | 5,675 | |
| - | - | |
| 0.0 | 3.4 | |
| about 3 years ago | 17 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Artifact_Removal_GAN
t81_558_deep_learning
-
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.
-
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
-
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!
-
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
What are some alternatives?
Deep-Learning - In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
RefinementGAN - Official implementation of the paper: https://arxiv.org/abs/2108.04957
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
DotA2-Icon-GAN - Using GANs to generate DotA2 Ability Icons
pix2pix - This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
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, ... 🧠
handwritten-digits-recognizer-webapp - This is my first experience with machine learning