Automated Machine Learning for Predictive Modeling

Auger.AI - The Power Tool For Machine Learning:

Faster, more accurate.

Auger offers the industry's most accurate Automated Machine Learning. It intelligently traverses the infinite space of algorithm/hyperparameter combinations to find the best possible predictive models faster.

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Analysts, data scientists and developers can manage the features, target and algorithms attempted for their dataset via Auger’s easy to use model manager. Learn more

See Auger In Action!

 

Who is using us?

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Auger provides the most accurate Automated Machine Learning solution within bounded timeframes.

Our Impact

 
 

In the example above we ran Auger against other leading AutoML tools using Microsoft’s own 89 datasets chosen to highlight their accuracy. Auger’s error rate on these difficult classification problems was less than 20%, reducing errors from Azure and Google’s AutoML by more than 20%. On more representative datasets the advantage is larger.

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How it Works

How the Auger Automated Machine Learning process works.

The user provides structured data via CSV files or relational databases.

The user provides structured data via CSV files or relational databases.

They identify the target and contributing features and Auger determines whether it's a regression, classification or time series experiment.

They identify the target and contributing features and Auger determines whether it's a regression, classification or time series experiment.

Auger then preprocesses the data: imputing missing values, removing overly sparse, low variances and over-correlated features, and generating additional features using a variety of heuristics.

Auger then preprocesses the data: imputing missing values, removing overly sparse, low variances and over-correlated features, and generating additional features using a variety of heuristics.

Auger searches through thousands of algorithms and hyperparameters to find the best performing models and creates ensembles to further improve accuracy.

Auger searches through thousands of algorithms and hyperparameters to find the best performing models and creates ensembles to further improve accuracy.

The results are presented in a leaderboard in real-time for the user to view and interpret.

The results are presented in a leaderboard in real-time for the user to view and interpret.

The user selects a winning model to deploy. Auger creates a web service prediction endpoint to generate predictions or classifications from new data encountered.

The user selects a winning model to deploy. Auger creates a web service prediction endpoint to generate predictions or classifications from new data encountered.