practical ml
1.0.0
"Progress is a natural result of staying focused on the process of doing anything." - Thomas Sterner, The Practicing Mind
Pratical ML is a collection of Jupyter notebooks where one can learn by example and actively practice training state-of-the-art machine learning models and algorithms.
To get started, find a task you are interested in below and hit the button on that row or hit the article button if you prefer to read instead.
Task | Dataset | Model | Notebook | |
---|---|---|---|---|
Anime Character GAN | Private | StyleGAN2 | ||
Anime Super Resolution | Private | Waifu2x+CARN | ||
Art Generation | WikiArt | v-diffusion+CLIP | ||
Detect People From Images | COCO | YOLOv5 | ||
Document Image Classification | RVL-CDIP | DiT | ||
Face Super Resolution | Private | Real-ESRGAN | ||
Face to Anime | Dataset-1 | AnimeGANv2 | ||
Optical Character Recognition | SROIE | TrOCR | ||
Remove Image Background | VOC2012 | DeepLabV3 |
Task | Dataset | SOTA | SOTA Acc | Our Acc | Notebook | |
---|---|---|---|---|---|---|
Hate Speech Detection | Dynabench | Leaderboard | - | 86.6 | ||
Named Entity Recognition | BC5CDR | Nooralahzadeh et al. (2019) | 89.9 | 89.3 | ||
Named Entity Recognition | CoNLL++ | Wang et al. (2019) | 94.3 | 93.5 | ||
Named Entity Recognition (CN) | MSRA | Zhang et al. (2018) | 93.2 | 93.9 | ||
Named Entity Recognition (CN) | WEIBO_1K | Peng et al. (2016) | 47 | 67.5 | ||
Sarcarsm Detection | Cai et al. (2019) | Pan et al. (2020) | 82.9 | 92.2 | ||
Sentiment Analysis | IMDB | Yang et al. (2019) | 96.2 | 92.2 | ||
Sentiment Analysis (CN) | WAIMAI_10K | BERT | 89 | 91.5 |
Task | Dataset | Model | Notebook | |
---|---|---|---|---|
Mandarin Text-to-Speech | DataBaker | Tacotron2-DDC-GST | ||
Singlish Text-to-Speech | IMDA | FastSpeech2+MelGAN | ||
Text-to-Speech | LJ Speech | Tacotron2+WaveGlow | ||
Text-to-Speech | Private | SileroTTS | ||
Video Subtitling | LibriSpeech | Wav2Vec2 | ||
Video Subtitling | Private | Whisper |
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind are welcome!
MIT
If you want to cite practical-ml
, use the following Bibtex entry:
@misc{siow2020practicalml,
title={Practical Machine Learning: A Collection of Machine Learning Experiments in Notebooks},
author={Eugene Siow},
year={2020},
url={https://github.com/eugenesiow/practical-ml},
note={Available at: https://github.com/eugenesiow/practical-ml}
}