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Automated Machine Learning

What is automated machine learning?

Automated machine learning (AutoML) is the process of solving real-world challenges by automating AI-based machine learning—which uses statistical techniques or algorithms to enable a computer to become better at what it does. AutoML runs the entire machine learning gamut end to end, from raw dataset to deployable machine learning model.

AutoML software automates multiple machine learning functions, including discovering patterns and structures, finding unusual data points, predicting values and categories, and solving a variety of problems.

What are the business benefits of automated machine learning?

Among the multiple business benefits of AutoML are:

  • Allowing businesses to consume and make sense of very large amounts of data from a variety of sources.
  • Enabling non-experts to easily implement machine learning models, techniques and solutions, freeing an organization’s data scientists to focus on more complex problems.
  • Accelerating the delivery of simpler solutions that often outperform manually designed models.
  • Solving more business problems faster by automating manual, tedious tasks—such as comparing dozens of models to unearth insights and predictions—that would otherwise require weeks or months of data scientists’ time.
  • Improving data science ROI by leveraging the institutional knowledge of data scientists and avoiding the time and cost required to capture value.

Automated Machine Learning Featured Content
Four Ways Evolutionary AI Can Extend AI’s Problem-Solving Capacity
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Machine Learning: The First Salvo of the AI Business Revolution

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