pytorch-widedeep
tabnet
| pytorch-widedeep | tabnet | |
|---|---|---|
| 7 | 8 | |
| 1,238 | 2,482 | |
| - | 0.7% | |
| 8.5 | 4.8 | |
| 7 days ago | 3 months 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
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why can't I import pytorch-widedeep ?
Ask the dev https://github.com/jrzaurin/pytorch-widedeep/issues
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[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
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[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)
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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:
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[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
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[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.
tabnet
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Time series data into a CNN
There's architectures that operate on tabular data from a few years back now that uses CNN's and self attention. .look at tabnet for inspiration: https://github.com/dreamquark-ai/tabnet
- [P] Stable Diffusion in Tensorflow / Keras
- [D] Opinions about TabNet
- Deep Learning Models to do Regression on a Tabular Data
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Tried so many different models but cant get good accuracy
I tried some other projects like [tabnet](https://github.com/dreamquark-ai/tabnet) they are also yielding *decent* results, but not more than 0.64.
- [P] pytorch-widedeep v1.0.9: the Perceiver and the FastFormer for tabular data are now available in the library
- [D] Why Neural Networks for tabular data are bad?
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Feature Importance in Multiclass problems
Are you solving a tabular problem? If it is so, you can use TabNet to plot them. It also supports multiclass and multilabel.
What are some alternatives?
alibi-detect - Algorithms for outlier, adversarial and drift detection
tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]
autogluon - Fast and Accurate ML in 3 Lines of Code
torchio - Medical imaging toolkit for deep learning
Linear-Multihead-Attention - Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
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.
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
ExtractTable-py - Python library to extract tabular data from images and scanned PDFs
LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.