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Adaptive Experimentation Platform

Why Ax?Get startedTutorials

Key Features

Modular

Modular

Easy to plug in new algorithms and use the library across different domains.

Supports A/B Tests

Supports A/B Tests

Field experiments require a range of considerations beyond standard optimization problems.

Production-Ready

Production-Ready

Support for industry-grade experimentation and optimization management, including MySQL storage.

Get Started

  1. Install Ax:
    pip3 install ax-platform
  2. Run an optimization:

    >>> from ax import optimize
    >>> best_parameters, best_values, experiment, model = optimize(
    parameters=[
    {
    "name": "x1",
    "type": "range",
    "bounds": [-10.0, 10.0],
    },
    {
    "name": "x2",
    "type": "range",
    "bounds": [-10.0, 10.0],
    },
    ],
    # Booth function
    evaluation_function=lambda p: (p["x1"] + 2*p["x2"] - 7)**2 + (2*p["x1"] + p["x2"] - 5)**2,
    minimize=True,
    )

    >>> best_parameters
    {'x1': 1.02, 'x2': 2.97} # true min is (1, 3)