autokeras
autogluon
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| autokeras | autogluon | |
|---|---|---|
| 5 | 8 | |
| 9,065 | 7,091 | |
| 0.2% | 3.3% | |
| 5.3 | 9.6 | |
| about 1 month ago | 7 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.
autokeras
- Machine Learning Algorithms Cheat Sheet
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Ask HN: Which piece of tech is underutilized?
I think the interfaces aren't high level enough for the average programmer to adopt it. It needs what https://autokeras.com is for neural nets.
- Technical documentation that just works
- SVM training taking forever on my local machine. Will using AWS Sagemaker be faster for training SVM (Linear) models?
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[D] [P] How do you use tools like AutoML?
AutoKeras time_series_forecaster.py
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?
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
adanet - Fast and flexible AutoML with learning guarantees.
auto-sklearn - Automated Machine Learning with scikit-learn
tf-keras-vis - Neural network visualization toolkit for tf.keras
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
automlbenchmark - OpenML AutoML Benchmarking Framework
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
NAS-Projects - Automated deep learning algorithms implemented in PyTorch. [Moved to: https://github.com/D-X-Y/AutoDL-Projects]