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Automlbenchmark Alternatives
Similar projects and alternatives to automlbenchmark
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mljar-supervised
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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ai-seed
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InfluxDB
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autoai
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
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automl-app
AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally!
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Ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better automlbenchmark alternative or higher similarity.
automlbenchmark reviews and mentions
Posts with mentions or reviews of automlbenchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-24.
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Show HN: Web App with GUI for AutoML on Tabular Data
Here is benchmark done by independent team of researchers https://openml.github.io/automlbenchmark/
I think most of overfitting is avoided with early stoppoing technique.
The underfitting can be avoidwd with using large training time.
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Show HN: AutoAI
Your list excludes most of well-known open-source AutoML tools such as auto-sklearn, AutoGluon, LightAutoML, MLJarSupervised, etc. These tools have been very extensively benchmarked by the OpenML AutoML Benchmark (https://github.com/openml/automlbenchmark) and have papers published, so they are pretty well-known to the AutoML community.
Regarding H2O.ai: Frankly, you don't seem to understand H2O.ai's AutoML offerings.
I'm the creator of H2O AutoML, which is open source, and there's no "enterprise version" of H2O AutoML. The interface is simple -- all you need to specify is the training data and target. We have included DNNs in our set of models since the first release of the tool in 2017. Read more here: https://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html We also offer full explainability for our models: https://docs.h2o.ai/h2o/latest-stable/h2o-docs/explain.html
H2O.ai develops another AutoML tool called Driverless AI, which is proprietary. You might be conflating the two. Neither of these tools need to be used on the H2O AI Cloud. Both tools pre-date our cloud by many years and can be used on a user's own laptop/server very easily.
Your Features & Roadmap list in the README indicates that your tool does not yet offer DNNs, so either you should update your post here or update your README if it's incorrect: https://github.com/blobcity/autoai/blob/main/README.md#featu...
Lastly, I thought I would mention that there's already an AutoML tool called "AutoAI" by IBM. Generally, it's not a good idea to have name collisions in a small space like the AutoML community. https://www.ibm.com/support/producthub/icpdata/docs/content/...
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Show HN: Mljar Automated Machine Learning for Tabular Data (Explanation,AutoDoc)
I'm also curious how does it compare! The package will be included in the newest comparison done by OpenML people https://github.com/openml/automlbenchmark
I have some old comparison of closed-source old system
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A note from our sponsor - WorkOS
workos.com | 18 Apr 2024
Stats
Basic automlbenchmark repo stats
3
378
6.9
11 days ago
openml/automlbenchmark is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of automlbenchmark is Python.
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