Python Automl

Open-source Python projects categorized as Automl | Edit details

Top 23 Python Automl Projects

  • Ray

    An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

    Project mention: Help needed to understand Rllib attention model parameters | reddit.com/r/reinforcementlearning | 2022-05-07

    Cross-posting the answer from the ray.io Discourse forum:

  • nni

    An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

    Project mention: Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI | dev.to | 2021-10-04

    For a complete tutorial, navigate to this Jupyter Notebook: https://github.com/microsoft/nni/blob/master/examples/notebooks/tabular_data_classification_in_AML.ipynb

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • autokeras

    AutoML library for deep learning

    Project mention: Machine Learning Algorithms Cheat Sheet | news.ycombinator.com | 2022-02-19
  • MindsDB

    In-Database Machine Learning

    Project mention: Show HN: PostgresML, now with analytics and project management | news.ycombinator.com | 2022-05-02
  • auto-sklearn

    Automated Machine Learning with scikit-learn

    Project mention: Why not AutoML every tabular data? | reddit.com/r/datascience | 2021-07-26

    Efficiency Ignoring the feature engineering aspects aside, a typical data scientist workflow involves trying out the different models. Some of the AutoML modules like H2O AutoML, AutoSklearn does this for you, and allow you to interpret your models. All these save so much time experimenting with the standard models.

  • autogluon

    AutoGluon: AutoML for Image, Text, and Tabular Data

    Project mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14

    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.

  • igel

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

    Project mention: Train/fit, test, and use models without writing code | reddit.com/r/ArtificialInteligence | 2021-06-29

    Link to the repo: https://github.com/nidhaloff/igel

  • SonarQube

    Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.

  • zenml

    ZenML 🙏: MLOps framework to create reproducible pipelines. https://zenml.io.

    Project mention: [D] Feedback on a worked Continuous Deployment Example (CI/CD/CT) | reddit.com/r/MachineLearning | 2022-04-12

    Hey everyone! At ZenML, we released today an integration that allows users to train and deploy models from pipelines in a simple way. I wanted to ask the community here whether the example we showcased makes sense in a real-world setting:

  • mljar-supervised

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

    Project mention: library / framework to test multiple sklearn regression models at once | reddit.com/r/algotrading | 2022-05-19

    If you need a simple and fast solution, go with auto-sklearn Maybe a bit more complex, but very powerful was mljar-supervised

  • AutoDL-Projects

    Automated deep learning algorithms implemented in PyTorch.

    Project mention: Forward pass computation for GDAS NAS coding | reddit.com/r/pytorch | 2021-06-06

    https://github.com/D-X-Y/AutoDL-Projects/issues/99#issuecomment-835802887

  • MLBox

    MLBox is a powerful Automated Machine Learning python library.

    Project mention: Feeling starting out | reddit.com/r/datascience | 2022-03-22
  • sparseml

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

    Project mention: [P] Compound sparsification: using pruning, quantization, and layer dropping to improve BERT performance | reddit.com/r/MachineLearning | 2021-10-20

    Hi u/_Arsenie_Boca_, definitely. Our recipes and sparse models along with the SparseZoo Python API to download them are open-sourced and the SparseZoo UI that can be used to explore them is free to use. The SparseML codebase to apply recipes enabling the creation of the sparse models is open sourced. The Sparsify codebase to create recipes through a UI is as well. And finally, the DeepSparse Engine's backend is closed sourced but free to use.

  • DeepCamera

    DeepCamera is not only an AI Face Recognition/Person Detection NVR. Machine Learning on the Edge, turn your Camera into AI-powered with Jetson Nano and telegram to protect your privacy.

  • AutoViz

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

  • SMAC3

    Sequential Model-based Algorithm Configuration

    Project mention: Finding the optimal parameter | reddit.com/r/compsci | 2022-02-25

    Apart from the aforementioned comments noting that this is an optimization problem, ready-to-use python libraries for this kind of problem (accounting for evaluation time) include http://hyperopt.github.io/hyperopt/, https://github.com/automl/SMAC3, or https://www.ray.io/ray-tune

  • PySR

    High-Performance Symbolic Regression in Python

    Project mention: ‘Machine Scientists’ Distill the Laws of Physics from Raw Data | news.ycombinator.com | 2022-05-10

    I found it curious that one of the implementations of symbolic regression (the "machine scientist" referenced in the article) is a Python wrapper on Julia: https://github.com/MilesCranmer/PySR

    I don't think I've seen a Python wrapper on Julia code before.

  • tods

    TODS: An Automated Time-series Outlier Detection System (by datamllab)

  • luminaire

    Luminaire is a python package that provides ML driven solutions for monitoring time series data.

    Project mention: luminaire: NEW Data - star count:570.0 | reddit.com/r/algoprojects | 2022-05-19
  • evalml

    EvalML is an AutoML library written in python.

    Project mention: library / framework to test multiple sklearn regression models at once | reddit.com/r/algotrading | 2022-05-19
  • FEDOT

    Automated modeling and machine learning framework FEDOT

    Project mention: Winning a Flood-Forecasting Hackathon with Hydrology and AutoML | reddit.com/r/hackathon | 2022-01-14

    Hi to everyone! I am a developer of the FEDOT framework, and our team and I (NSS_lab team) recently won a hackathon EmergencyDataHack (rus). There was a recent post on TowardsDataSciense based on our competition things: Winning a Flood-Forecasting Hackathon with Hydrology and AutoML.

  • tune-sklearn

    A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

    Project mention: LightGBM vs. XGBoost: Which distributed version is faster? | news.ycombinator.com | 2021-08-10

    Of course not! :)

    The Ray ecosystem is actually chalk full of integrations, from XGBoost Ray (https://docs.ray.io/en/master/xgboost-ray.html), to PyTorch on Ray (https://docs.ray.io/en/master/using-ray-with-pytorch.html), and of course hyperparameter search with Ray Tune for a variety of libraries, including Sklearn (https://github.com/ray-project/tune-sklearn).

  • lazypredict

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

    Project mention: Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning | reddit.com/r/learnmachinelearning | 2022-02-16
  • Auto_ViML

    Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

    Project mention: library / framework to test multiple sklearn regression models at once | reddit.com/r/algotrading | 2022-05-19
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). The latest post mention was on 2022-05-19.

Python Automl related posts

Index

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

Project Stars
1 Ray 20,487
2 nni 11,484
3 autokeras 8,498
4 MindsDB 6,766
5 auto-sklearn 6,275
6 autogluon 4,471
7 igel 2,980
8 zenml 1,974
9 mljar-supervised 1,895
10 AutoDL-Projects 1,378
11 MLBox 1,316
12 sparseml 960
13 DeepCamera 889
14 AutoViz 700
15 SMAC3 699
16 PySR 642
17 tods 571
18 luminaire 571
19 evalml 491
20 FEDOT 381
21 tune-sklearn 377
22 lazypredict 356
23 Auto_ViML 345
Find remote jobs at our new job board 99remotejobs.com. There are 7 new remote jobs listed recently.
Are you hiring? Post a new remote job listing for free.
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com