Deep-Learning-Experiments VS sudo_rm_rf

Compare Deep-Learning-Experiments vs sudo_rm_rf and see what are their differences.

Deep-Learning-Experiments

Videos, notes and experiments to understand deep learning (by roatienza)
Deep Learning deep-learning-tutorial Artificial intelligence Pytorch Vision Speech NLP
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sudo_rm_rf

Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of separating sources from mixtures. (by etzinis)
Deep Learning Speech speech-separation Audio
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Deep-Learning-Experiments sudo_rm_rf
1 1
1,081 299
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8.3 0.0
about 1 month ago 10 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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Deep-Learning-Experiments

Posts with mentions or reviews of Deep-Learning-Experiments. We have used some of these posts to build our list of alternatives and similar projects.
  • EEE 197 - Deep Learning
    1 project | /r/peyups | 25 Aug 2022
    Hello, took the course last sem. Maraming napa-drop sa amin dahil sa difficulty nung assignments pero doable naman. Open-source mismo yung course, available sya sa GitHub: https://github.com/roatienza/Deep-Learning-Experiments

sudo_rm_rf

Posts with mentions or reviews of sudo_rm_rf. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-05.

What are some alternatives?

When comparing Deep-Learning-Experiments and sudo_rm_rf you can also consider the following projects:

conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

stemroller - Isolate vocals, drums, bass, and other instrumental stems from any song

adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

demucs-cxfreeze

DeepLearning - Contains all my works, references for deep learning

TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

python_autocomplete - Use Transformers and LSTMs to learn Python source code

demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.

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, ... 🧠

vid2cleantxt - Python API & command-line tool to easily transcribe speech-based video files into clean text

pytorch-deepdream - PyTorch implementation of DeepDream algorithm (Mordvintsev et al.). Additionally I've included playground.py to help you better understand basic concepts behind the algo.

Deep-Learning-Experiments vs conformal_classification sudo_rm_rf vs stemroller Deep-Learning-Experiments vs adaptnlp sudo_rm_rf vs demucs-cxfreeze Deep-Learning-Experiments vs DeepLearning sudo_rm_rf vs TTS Deep-Learning-Experiments vs python_autocomplete sudo_rm_rf vs demucs Deep-Learning-Experiments vs nn sudo_rm_rf vs vid2cleantxt Deep-Learning-Experiments vs pytorch-deepdream Deep-Learning-Experiments vs TTS