FLAML

6.5easy start · #9 of 36
in Predictive Analytics Software

Free to practise onnot on record
Free trialnot on record
Well documentedyes
Runs where you workyes

Runs on api, Linux, Mac, self-hosted, Windows.

FLAML is ranked #9 of 36 in predictive analytics software on The Geeks Club. It runs on API, Linux, macOS, Self-hosted, Windows.

Compared on predictive analytics software

Free plan: Yes

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The record

Purpose: FLAML is a fast library for automated machine learning and tuning.
Resource efficiency: It finds accurate models or configurations for common ML/AI tasks with low computational resources.
LLM adaptation: FLAML automatically adapts large language models to applications to reduce monetary costs.
Auto-tuning: Its tuning approach handles large search spaces, heterogeneous evaluation costs, complex constraints, guidance, and early stopping.
Supported tasks: Task-oriented AutoML supports classification, regression, time-series forecasting, panel forecasting, learning to rank, and sequence classification.
Zero-shot AutoML: The flaml.default package recommends data-dependent hyperparameter defaults without runtime tuning.
Python requirement: The installation documentation requires Python version 3.10 or newer.
Model integrations: Optional installations include OpenAI models, CatBoost, Vowpal Wabbit, Prophet, statsmodels, and Hugging Face Transformers.
Distributed integrations: FLAML provides optional Ray and Spark distributed tuning, plus NNI, BlendSearch, and Azure Synapse options.
.NET support: FLAML has a .NET implementation in the cross-platform ML.NET framework, including Model Builder, the ML.NET CLI, and Microsoft.ML.AutoML.
Spark limitation: GPU training is not supported when Spark is used as the parallel backend.
License: The repository is distributed under the MIT License, permitting users to use, copy, modify, publish, distribute, sublicense, and sell the software subject to its conditions.
Security reporting: The project directs security vulnerability reports to Microsoft Security Response Center for coordinated disclosure rather than public issues.
Community support: The project provides community support through Discord, issues, discussions, and contributions.

Where it ranks on The Geeks Club

Best Predictive Analytics Software in 2026#9 of 36
Best AutoML Software in 2026#11 of 28

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Sources

microsoft.github.io/FLAML/· checked 1 Oct 2026
microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-Auto· checked 1 Oct 2026
microsoft.github.io/FLAML/docs/Use-Cases/Zero-Shot-AutoML/· checked 1 Oct 2026
microsoft.github.io/FLAML/docs/Installation/· checked 1 Oct 2026
microsoft.github.io/FLAML/docs/Examples/Integrate%20-%20Spa· checked 1 Oct 2026
github.com/microsoft/FLAML/blob/main/LICENSE· checked 1 Oct 2026
github.com/microsoft/FLAML/security· checked 1 Oct 2026
microsoft.github.io/FLAML/docs/Contribute/· checked 1 Oct 2026
github.com/microsoft/FLAML· checked 2 Oct 2026
microsoft.github.io/FLAML/docs/Examples/Integrate%20-%20Azu· checked 2 Oct 2026
github.com/microsoft/FLAML/blob/main/pyproject.tom· checked 2 Oct 2026