Top 23 neural-network Open-Source Projects
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Project mention: [D] How is it checked if models do not just memorize their training examples? | reddit.com/r/MachineLearning | 2022-04-28
But there's a nice survey on Arxiv here of various deepfake / face swap methods. Some of methods listed in the table on page 4, such as Faceswap and Faceswap-GAN, apparently use encoder-decoder models. I think Faceswap-GAN was the one that I was thinking of in particular; apparently it adds a perceptual loss and an adversarial loss to an autoencoder.
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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DeepFaceLab
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I was going through this example of a LSTM language model on github (link).What it does in general is pretty clear to me. But I'm still struggling to understand what calling contiguous() does, which occurs several times in the code.
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Given your need, I think you'll be better off with libraries like Spacy, which does NLP (rather than just DNN inference). You'll get your app much faster this way.
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DeepSpeech
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Project mention: Show HN: State-of-the-Art German Speech Recognition in 284 lines of C++ | news.ycombinator.com | 2022-08-10I wrote "284 lines of C++" to indicate that this is compact enough for people to actually read and understand the source code. Also, compiling my implementation is super easy and straightforward ... something which can't be said for Kaldi, Vosk, or DeepSpeech.
If you try to read the CTC beam search decoder from Mozilla's DeepSpeech [1], that alone is about 2000 LOC in multiple files.
If you try to read the pyctcdecode source that is used by HuggingFace [2], that's 1000+ LOC of Python.
But this implementation is all the client-side, i.e. the entire "native_client" folder hierarchy in DeepSpeech [3], narrowed down to a mere 284 lines.
[1] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...
[2] https://github.com/kensho-technologies/pyctcdecode
[3] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...
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Project mention: How to convert a low resolution, pixelated image into a high resolution picture 💫 | reddit.com/r/lifehacks | 2022-07-15
Or use qaifu2x or Anime4K
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Project mention: How to simulate a robot along with physics in Unity3D? | reddit.com/r/Unity3D | 2022-07-12This repo might help. There are additional resources listed as well.
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Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
Project mention: Reach out to me for python (ML/DL) related issues , Will be happy to help | reddit.com/r/learnprogramming | 2021-09-11hands on machine learning (paid ) For free resources check this github repo it has collection of materials to study. you can follow this in reference to this roadmap that way you are kind of on straight path
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nn
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Project mention: [P] Fine-tuned the GPT-Neox Model to Generate Quotes | reddit.com/r/MachineLearning | 2022-08-11Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/neox
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Project mention: Where to learn how to turn photos into images in the style of famous painters? | reddit.com/r/MediaSynthesis | 2021-10-25
Try: https://github.com/lengstrom/fast-style-transfer . There are links to the underlying papers.
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Cursory search reveals this github with a summary of some of the field, last updated in May of this year
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Project mention: Question about including parent directory C++ files in Rust crate | reddit.com/r/rust | 2022-08-09
So I am working on moving the onnxruntime bindings upstream to https://github.com/microsoft/onnxruntime. The directory structure I have is
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Project mention: Environments that require long-term memory and reasoning | reddit.com/r/reinforcementlearning | 2022-05-30
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Project mention: Pyod – A Comprehensive and Scalable Python Library for Outlier Detection | news.ycombinator.com | 2022-08-10
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Project mention: Dice Score not decreasing when doing semantic segmentation | reddit.com/r/learnmachinelearning | 2022-04-17
When i pass the CT-Scans and the masks to the Loss Function, which is the Jaccard-Loss from the segmentation_models.pytorch library, the value does not decrease but stay in the range of 1.0-0.9 over 50 epochs training on only one batch of 32 images. As far as I have understood, my network should overfit and the loss should decrease since I am only training on one batch of a small amount of images. However this does not happen. I also tried more batches with all the data over 100 epochs, but the loss does not decrease either obviously. Does anyone have an idea what I might have done wrong? Do I have to change anything when passing the masks to my loss function?
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I remember that there was a lecture in the MIT intro course. https://github.com/aamini/introtodeeplearning/tree/master/lab1
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Learn-Datascience-For-Free
This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in Twitter.
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There are many good options when it comes to tools and libraries for implementing data augmentation into our deep learning pipeline. You could for instance do your own augmentations using NumPy or Pillow. Some of the most popular dedicated libraries for image augmentation include Albumentations, imgaug, and Augmentor. Both TensorFlow and PyTorch even come with their own packages dedicated to image augmentation.
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2) Flux treats softmax a little different than most other activation functions (see here for more details) such as relu and sigmoid. When you pass an activation function into a layer like Dense(3, 32, relu), Flux expects that the function is broadcast over the layer's output. However, softmax cannot be broadcast as it operates over vectors rather than scalars. This means that if you want to use softmax as the final activation in your model, you need to pass it into Chain() like so:
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Project mention: Bayesian Hierarchical Models for algorithmic trading? | reddit.com/r/algotrading | 2022-06-08
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Index
What are some of the best open-source neural-network projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Keras | 55,881 |
| 2 | faceswap | 41,942 |
| 3 | DeepFaceLab | 34,217 |
| 4 | pytorch-tutorial | 24,395 |
| 5 | spaCy | 23,929 |
| 6 | DeepSpeech | 20,016 |
| 7 | Anime4K | 15,094 |
| 8 | ml-agents | 13,220 |
| 9 | Machine-Learning-Tutorials | 12,238 |
| 10 | nn | 10,993 |
| 11 | fast-style-transfer | 10,512 |
| 12 | 3D-Machine-Learning | 8,137 |
| 13 | onnxruntime | 7,292 |
| 14 | lab | 6,730 |
| 15 | pyod | 6,066 |
| 16 | segmentation_models.pytorch | 5,923 |
| 17 | introtodeeplearning | 5,450 |
| 18 | Keras.js | 4,884 |
| 19 | Learn-Datascience-For-Free | 4,824 |
| 20 | Augmentor | 4,769 |
| 21 | Flux.jl | 3,771 |
| 22 | probability | 3,753 |
| 23 | machine_learning_basics | 3,701 |
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