Deep-Learning-Experiments
pytorch-deepdream
| Deep-Learning-Experiments | pytorch-deepdream | |
|---|---|---|
| 1 | 3 | |
| 1,081 | 355 | |
| - | - | |
| 8.3 | 0.0 | |
| about 1 month ago | 8 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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Deep-Learning-Experiments
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EEE 197 - Deep Learning
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
pytorch-deepdream
What are some alternatives?
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).
fastai - The fastai deep learning library
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.
MLOps - MLOps examples
DeepLearning - Contains all my works, references for deep learning
python_autocomplete - Use Transformers and LSTMs to learn Python source code
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, ... 🧠
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
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.