autogluon VS FLAML

Compare autogluon vs FLAML and see what are their differences.

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autogluon FLAML
8 9
7,413 3,770
2.4% 1.1%
9.6 6.7
10 days ago about 1 month ago
Python Jupyter Notebook
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

autogluon

Posts with mentions or reviews of autogluon. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

FLAML

Posts with mentions or reviews of FLAML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-14.

What are some alternatives?

When comparing autogluon and FLAML you can also consider the following projects:

autokeras - AutoML library for deep learning

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

auto-sklearn - Automated Machine Learning with scikit-learn

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

nitroml - NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.

automlbenchmark - OpenML AutoML Benchmarking Framework

FEDOT - Automated modeling and machine learning framework FEDOT

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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.
www.influxdata.com
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