FLAML VS Made-With-ML

Compare FLAML vs Made-With-ML and see what are their differences.

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FLAML Made-With-ML
9 51
3,671 35,610
3.2% -
8.3 6.8
18 days ago 5 months ago
Jupyter Notebook Jupyter Notebook
MIT License 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.

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.

Made-With-ML

Posts with mentions or reviews of Made-With-ML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-25.

What are some alternatives?

When comparing FLAML and Made-With-ML you can also consider the following projects:

autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code

zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.

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

mlops-zoomcamp - Free MLOps course from DataTalks.Club

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.

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

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

practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book

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

Copulas - A library to model multivariate data using copulas.

FEDOT - Automated modeling and machine learning framework FEDOT

ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training