Python Automl

Open-source Python projects categorized as Automl

Top 23 Python Automl Projects

  • 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.

  • Project mention: Ray: Unified framework for scaling AI and Python applications | news.ycombinator.com | 2024-05-03
  • best-of-ml-python

    🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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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.

  • autokeras

    AutoML library for deep learning

  • auto-sklearn

    Automated Machine Learning with scikit-learn

  • autogluon

    Fast and Accurate ML in 3 Lines of Code

  • featuretools

    An open source python library for automated feature engineering

  • Project mention: Featuretools – A Python Library for Automated Feature Engineering | news.ycombinator.com | 2023-09-20
  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  • zenml

    ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

  • Project mention: FLaNK AI - 01 April 2024 | dev.to | 2024-04-01
  • statsforecast

    Lightning ⚡️ fast forecasting with statistical and econometric models.

  • Project mention: TimeGPT-1 | news.ycombinator.com | 2023-10-13

    I can't find the TimeGPT-1 model.

    LICENSE Apache-2

    https://github.com/Nixtla/statsforecast/blob/main/LICENSE

    Mentions ARIMA, ETS, CES, and Theta modeling

  • Merlion

    Merlion: A Machine Learning Framework for Time Series Intelligence

  • igel

    a delightful machine learning tool that allows you to train, test, and use models without writing code

  • mljar-supervised

    Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

  • Project mention: Show HN: Web App with GUI for AutoML on Tabular Data | news.ycombinator.com | 2023-08-24

    Web App is using two open-source packages that I've created:

    - MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised

    - Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury

    You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.

  • keras-tuner

    A Hyperparameter Tuning Library for Keras

  • lazypredict

    Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

  • Auto-PyTorch

    Automatic architecture search and hyperparameter optimization for PyTorch

  • Project mention: [Project] AMLTK: A framework for building your own AutoML (AutoSklearn authors) | /r/MachineLearning | 2023-12-09

    We took some of the lessons learned while building AutoSklearn and AutoPytorch, the good, the bad and the ugly and made a library that to enable the next generation of open-source AutoML tools, to allow them to be research-able but also efficient and scalable. We have some future plans and on-going work with this and we'd like to gather any feedback the community might have!

  • sparseml

    Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

  • PySR

    High-Performance Symbolic Regression in Python and Julia

  • Project mention: Potential of the Julia programming language for high energy physics computing | news.ycombinator.com | 2023-12-04

    > Yes, julia can be called from other languages rather easily

    This seems false to me. StaticCompiler.jl [1] puts in their limitations that "GC-tracked allocations and global variables do not work with compile_executable or compile_shlib. This has some interesting consequences, including that all functions within the function you want to compile must either be inlined or return only native types (otherwise Julia would have to allocate a place to put the results, which will fail)." PackageCompiler.jl [2] has the same limitations if I'm not mistaken. So then you have to fall back to distributing the Julia "binary" with a full Julia runtime, which is pretty heavy. There are some packages which do this. For example, PySR [3] does this.

    There is some word going around though that there is an even better static compiler in the making, but as long as that one is not publicly available I'd say that Julia cannot easily be called from other languages.

    [1]: https://github.com/tshort/StaticCompiler.jl

    [2]: https://github.com/JuliaLang/PackageCompiler.jl

    [3]: https://github.com/MilesCranmer/PySR

  • AutoViz

    Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

  • AutoDL-Projects

    Automated deep learning algorithms implemented in PyTorch.

  • EasyRec

    A framework for large scale recommendation algorithms.

  • Project mention: FLaNK Stack Weekly for 20 June 2023 | dev.to | 2023-06-20

    Recommendation Framework https://github.com/alibaba/EasyRec

  • MLBox

    MLBox is a powerful Automated Machine Learning python library.

  • tods

    TODS: An Automated Time-series Outlier Detection System

  • SMAC3

    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

Python Automl related posts

  • Show HN: ai() to run any ML and answer with Python type

    1 project | news.ycombinator.com | 10 Apr 2024
  • Fine-tuning a Mistral Language Model with Anyscale

    2 projects | dev.to | 1 Feb 2024
  • MindsDB Docker Extension: Build ML powered apps at a much faster pace

    3 projects | dev.to | 1 Jan 2024
  • Using Large Language Models for Hyperparameter Optimization, Zhang et al. 2023 [GPT-4 is quite good at finding the optimal hyperparameters for machine learning tasks]

    2 projects | /r/mlscaling | 10 Dec 2023
  • [Project] AMLTK: A framework for building your own AutoML (AutoSklearn authors)

    2 projects | /r/MachineLearning | 9 Dec 2023
  • functime: NEW Data - star count:616.0

    1 project | /r/algoprojects | 8 Nov 2023
  • functime: NEW Data - star count:601.0

    1 project | /r/algoprojects | 22 Oct 2023
  • A note from our sponsor - InfluxDB
    www.influxdata.com | 26 May 2024
    Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality. Learn more →

Index

What are some of the best open-source Automl projects in Python? This list will help you:

Project Stars
1 Ray 31,493
2 best-of-ml-python 15,702
3 nni 13,813
4 autokeras 9,084
5 auto-sklearn 7,430
6 autogluon 7,201
7 featuretools 7,080
8 zenml 3,694
9 statsforecast 3,599
10 Merlion 3,281
11 igel 3,080
12 mljar-supervised 2,947
13 keras-tuner 2,837
14 lazypredict 2,729
15 Auto-PyTorch 2,297
16 sparseml 1,991
17 PySR 1,982
18 AutoViz 1,643
19 AutoDL-Projects 1,546
20 EasyRec 1,521
21 MLBox 1,479
22 tods 1,304
23 SMAC3 1,020

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