autogluon
tabnet
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| autogluon | tabnet | |
|---|---|---|
| 8 | 8 | |
| 7,050 | 2,474 | |
| 2.7% | 1.9% | |
| 9.6 | 4.8 | |
| 4 days ago | 2 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.
autogluon
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pip install remyxai - easiest way to create custom vision models
This seems not very convincing. There are other popular frameworks that provide AutoML with existing datasets (eg https://github.com/autogluon/autogluon)
- autogluon: NEW Data - star count:5070.0
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[D] Where is AutoML for NNs?
https://github.com/awslabs/autogluon works well for image/text/tabular data
- k-fold bagging in Autogluon - Tabular
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What will the data science job market be like in 5 years?
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
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?
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch
autokeras - AutoML library for deep learning
pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
auto-sklearn - Automated Machine Learning with scikit-learn
Linear-Multihead-Attention - Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
automlbenchmark - OpenML AutoML Benchmarking Framework
ExtractTable-py - Python library to extract tabular data from images and scanned PDFs