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Automated ML

Paid

Create ML models easily, accelerate development with pre-built models and templates, and monitor performance with analytics tools.

Type
Saas
Founded
2013

About Automated ML

Automated ML is an AI-based platform designed to simplify and speed up the machine learning workflow. It provides users with the tools to quickly and easily build, deploy, and manage powerful machine learning models for any application. Automated ML’s intuitive drag-and-drop interface allows users to quickly create sophisticated models with just a few clicks. It also includes a variety of pre-built models and templates tailored to specific applications, so users can get up and running quickly. Automated ML makes it easy for developers and data scientists to get their machine learning projects up and running in no time. The platform also includes a powerful set of analytics and monitoring tools to ensure that models are running optimally. With Automated ML, users can quickly and easily build powerful machine learning models without the need for deep technical expertise.

Key Features

Create powerful ML models with drag-and-drop interface.
Accelerate development with pre-built models and templates.
Monitor performance with powerful analytics tools.

Pros & Cons

Pros
  • Cutting-edge research from top universities
  • Open-source tools available
  • Strong funding and industry partnerships
Cons
  • Not a commercial SaaS product
  • Primarily academic focus, may not offer user-friendly GUI

Best For

Create powerful ML models with drag-and-drop interface.Accelerate development with pre-built models and templates.Monitor performance with powerful analytics tools.

Alternatives to Automated ML

FAQ

What is AutoML?
AutoML (Automated Machine Learning) targets progressive automation of machine learning to make it more accessible and efficient.
Who runs automl.org?
The website represents the research groups of Prof. Frank Hutter (Freiburg), Prof. Marius Lindauer (Hannover), and Dr. Katharina Eggensperger (Tübingen).
What tools do the groups develop?
They develop open-source tools for hyperparameter optimization, neural architecture search, and dynamic algorithm configuration.