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mljar-supervised reviews and mentions
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[P] Build data web apps in Jupyter Notebook with Python only
Sure, at the bottom of our website you can subscribe for newsletter.
- Show HN: AutoML Python Package for Tabular Data with Automatic Documentation
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library / framework to test multiple sklearn regression models at once
If you need a simple and fast solution, go with auto-sklearn Maybe a bit more complex, but very powerful was mljar-supervised
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Learning Python tricks by reading other people's code. But who?
MLJAR AutoML is a Python package for Automated Machine Learning on tabular data with feature engineering, explanations, and automatic documentation.
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'start with a simple model'
I recommend trying my AutoML package. You can easily check many different algorithms. Waht is more, the baseline algorithms are checked (major class predictor for classification and mean predictor for regression). The advance of AutoML is that it is really quick. You dont need to write preprocessing code, just call fit method.
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I'm Looking to Help Contribute, I am very confident with my skills
Automated Machine Learning (AutoML) Python package https://github.com/mljar/mljar-supervised You can check list of open issues. Or I can recommend some just tell me your preferences (Im the main contributor)
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[D] Bring your own data AI SaaS service for non-programmers?
Instead, we started to work on desktop application that will allow to create python notebooks with no-code GUI (https://github.com/mljar/studio some screenshots on our website ).
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What are some exciting new tools/libraries in 2021?
MLJAR AutoML for tabular data - https://github.com/mljar/mljar-supervised - it has automatic documentation for created models
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Is it possible to clean memory after using a package that has a memory leak in my python script?
I'm working on the AutoML python package (Github repo). In my package, I'm using many different algorithms. One of the algorithms is LightGBM. The algorithm after the training doesn't release the memory, even if del is called and gc.collect() after. I created the issue on LightGBM GitHub -> link. Because of this leak, memory consumption is growing very fast during algorithm training.
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What's your best use of AutoML?
In the MLJAR AutoML (https://github.com/mljar/mljar-supervised) you have mode Explain which is designed to explain data with ML. With this mode you will get a lot of explanations for your data: SHAP plots, decision tree visualization, decision rules in text format, feature importance. If you run the AutoML in Compete mode the Golden Features will be searched and constructed, maybe you will find some new features that have meaning for the business. In case of any questions, I'm happy to help!
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A note from our sponsor - Sonar
www.sonarsource.com | 24 Mar 2023
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mljar/mljar-supervised is an open source project licensed under MIT License which is an OSI approved license.