Hands-On-Meta-Learning-With-Python
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow (by sudharsan13296)
t81_558_deep_learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis (by jeffheaton)
| Hands-On-Meta-Learning-With-Python | t81_558_deep_learning | |
|---|---|---|
| 2 | 10 | |
| 1,123 | 5,671 | |
| - | - | |
| 0.0 | 3.4 | |
| over 2 years ago | 9 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | GNU General Public License v3.0 or later |
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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.
Hands-On-Meta-Learning-With-Python
Posts with mentions or reviews of Hands-On-Meta-Learning-With-Python.
We have used some of these posts to build our list of alternatives
and similar projects.
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I had Bing chat try to tackle a coding solution... can't tell if there's anything of value in here. Thoughts?
To implement the self-replication mechanism, I will use pickle2 as the main module for copying and initializing the artificial intelligence. Pickle is a module that can serialize and deserialize Python objects, such as classes, functions, or models. Pickle can also store and load the state of the objects, such as their attributes, parameters, or variables.
- What are the current programming challenges to AI, AGI and the such?
t81_558_deep_learning
Posts with mentions or reviews of t81_558_deep_learning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-27.
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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
What are some alternatives?
When comparing Hands-On-Meta-Learning-With-Python and t81_558_deep_learning you can also consider the following projects:
machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
EfficientWord-Net - OneShot Learning-based hotword detection.
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
DotA2-Icon-GAN - Using GANs to generate DotA2 Ability Icons
alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Artifact_Removal_GAN - A U-net GAN for jpeg artifact removal
SBERT-for-Question-Answering-on-COVID-19-Dataset - Sentence Bert for Question-Answering on COVID-19 Open Research Dataset (CORD-19)
handwritten-digits-recognizer-webapp - This is my first experience with machine learning
Hands-On-Meta-Learning-With-Python vs machine-learning-experiments
t81_558_deep_learning vs dnn_from_scratch
Hands-On-Meta-Learning-With-Python vs EfficientWord-Net
t81_558_deep_learning vs image-super-resolution
Hands-On-Meta-Learning-With-Python vs super-resolution
t81_558_deep_learning vs DotA2-Icon-GAN
Hands-On-Meta-Learning-With-Python vs alpha-zero-general
t81_558_deep_learning vs Artifact_Removal_GAN
Hands-On-Meta-Learning-With-Python vs SBERT-for-Question-Answering-on-COVID-19-Dataset
t81_558_deep_learning vs handwritten-digits-recognizer-webapp