pytorch-widedeep
rtdl
| pytorch-widedeep | rtdl | |
|---|---|---|
| 7 | 5 | |
| 1,238 | 314 | |
| - | - | |
| 8.5 | 8.9 | |
| 6 days ago | about 2 years ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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.
pytorch-widedeep
-
why can't I import pytorch-widedeep ?
Ask the dev https://github.com/jrzaurin/pytorch-widedeep/issues
-
[P] pytorch-widedeep model alert: TabPerceiver and TabFastFormer are now available in the library
New DL models for Tabular Data and functionalities added to the pytorch-widedeep library
-
[P] pytorch-widedeep model alert: SAINT and the FT-Transformer are now available in the library
🚨MODEL ALERT! 🚨New DL models for Tabular Data added to the pytorch-widedeep library . SAINT by Gowthami Somepalli and collaborators (paper: https://arxiv.org/abs/2106.01342) and the FT-Transformer which was already used at the SAINT paper but officially introduced by Yury Gorishniy and collaborators (paper: https://arxiv.org/abs/2106.11959). More functionalities coming soon to the [library](https://github.com/jrzaurin/pytorch-widedeep)
-
How to do K-Fold Cross Validation for hyperparameter tuning on pytorch-widedeep ?
Now in pytorch-widedeep (https://github.com/jrzaurin/pytorch-widedeep) the recommended path for training a single model is:
-
[P] pytorch-widedeep v1.0: deep learning for tabular data that you can combine with images and text
Main repo
- Pytorch-widedeep v1.0: deep learning for tabular data
-
[P] pytorch-widedeep, deep learning for tabular data: Deep Learning vs LightGBM
A thorough comparison between Deep Learning algorithms for tabular data (using pytorch-widedeep ) and LightGBM for classification and regression problems.
rtdl
-
[Project] Improving deep learning for tabular data with numerical embeddings (FT-Transformer)
Found relevant code at https://github.com/yandex-research/rtdl + all code implementations here
- [P] pytorch-widedeep v1.0.9: the Perceiver and the FastFormer for tabular data are now available in the library
- [P] pytorch-widedeep model alert: SAINT and the FT-Transformer are now available in the library
- [R] Revisiting Deep Learning Models for Tabular Data
What are some alternatives?
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch
alibi-detect - Algorithms for outlier, adversarial and drift detection
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
torchio - Medical imaging toolkit for deep learning
ArtLine - A Deep Learning based project for creating line art portraits.
scrambpy - Scramb.py is a region based JPEG Image Scrambler and Descrambler written in Python for End-to-End-Encrypted (E2EE) Image distribution through unaware channels.
best_AI_papers_2021 - A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
autogluon - Fast and Accurate ML in 3 Lines of Code
LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence
rtdl-num-embeddings - (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning