Solving business problems with "Prediction Engineering"
Translating a business need into a technical prediction problem definition usually requires many iterations. While use cases are similar, the data and processes required to harness predictive models can vary between large enterprises. Feature Labs offers a flexible interface to define and predict any future "event" of interest to an organization. After building a simple predictive model, the prediction can be refined to answer questions like:
Automated Feature Engineering
Most machine learning companies expect data to appear cleanly-formatted as a single table with one column used to predict all of the others. However, many datasets are actually observations collected over time and do not fit this format.
To make future predictions, Feature Labs extracts patterns from our historical data -- and does it automatically for any relational and time series dataset using our proprietary algorithm called Deep Feature Synthesis. This enables users to obtain the accuracy levels of human data scientists in 1/10th of the time.
Easy Model Deployment
Data on its own doesn’t do much; it must be used and used well. Return on investment only occurs when organizations operationalize and integrate their developed predictive models. We designed Feature Labs to make it possible to transition from exploratory work to production -- and to do it effortlessly. Once your work is in production, it's easy to retrain using new data, to adjust modeling parameters, and to evaluate your performance with confidence.