pytorch-adapt
autogluon
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| pytorch-adapt | autogluon | |
|---|---|---|
| 3 | 8 | |
| 323 | 7,091 | |
| - | 3.3% | |
| 0.0 | 9.6 | |
| about 1 year ago | 9 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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-adapt
- PyTorch-adapt re-purposes existing ML models to work in new domains
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[P] A domain adaptation library that I wrote: PyTorch Adapt
For more details, you might be interested in the jupyter notebooks here: https://github.com/KevinMusgrave/pytorch-adapt/blob/main/examples/README.md
I wrote [a library](https://github.com/KevinMusgrave/pytorch-adapt) for domain adaptation, which is a type of machine learning that repurposes existing models to work in new domains. A toy example is adapting a model trained on MNIST for use on colored digits:
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?
hierarchical-domain-adaptation - Code of NAACL 2022 "Efficient Hierarchical Domain Adaptation for Pretrained Language Models" paper.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
pykale - Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the ð¥PyTorch ecosystem. â Star to support our work!
autokeras - AutoML library for deep learning
Transfer-Learning-Library - Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
auto-sklearn - Automated Machine Learning with scikit-learn
CEPC - A domain adaptation model
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]
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