Web front-end for Best Buy Product Search demo – you can now interact directly with the Antelope application in a lightweight but realistic implementation that includes predictive input completion.This remains a demonstration release designed to expose the API and programming style, but things have moved along quite a bit since the first release (v0.1, November 2014). You may also wish to review the Frequently Asked Questions. Be sure to check out the Feature Engineering section to understand the core elements of working with Antelope. The Antelope Documentation remains a work in progress but provides additional perspectives. Try the Dating Simulation to further explore the richness of Antelope’s feature engineering capabilities. ![]() Check out Running the Best Buy Web Demo to see the predictive engine embedded in a working web application.First see the Getting Started with the Best Buy Demo instructions to download the Kaggle data and to run a simple machine learning exercise.We have provided two main examples, one that works with Kaggle competition data, the ACM SF Chapter’s Best Buy data set, and another that simulates dating site user behavior, attempting to replicate some of what we observe on our products. Perhaps the best way to understand Antelope is to give it a quick try. We’re releasing Antelope now because we want your feedback! Please join theĭon’t hesitate to post your questions, suggestions, or ideas. Machine learning model with the software used to run that model in production, a much If(we) to develop recommendation engines for our social products, hi5 and Tagged.īy unifying the software that data scientists use to extract data for training a It derives from a proprietary framework used by The Antelope Realtime Events project aims to make iterative and agile machine learningĪ practical reality, especially in systems that must repsond quickly to updated information.
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