saint
autogluon
| saint | autogluon | |
|---|---|---|
| 1 | 8 | |
| 366 | 7,181 | |
| - | 2.4% | |
| 1.8 | 9.6 | |
| over 2 years ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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.
saint
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[D] Tabular Data: Deep Learning is Not All You Need
SAINT paper emerges new, claiming that they have SOTA results than benchmarks, however, after only 2-3 weeks, people say that with fine tuning(not even feature engineering) they can have better results than proposed paper https://github.com/somepago/saint/issues/1 , on exactly same problems on paper.
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.
What are some alternatives?
trax - Trax — Deep Learning with Clear Code and Speed
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
mmocr - OpenMMLab Text Detection, Recognition and Understanding Toolbox
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
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
automlbenchmark - OpenML AutoML Benchmarking Framework
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
shapley - The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).