What Netflix’s newly open-sourced data science toolkit has to offer.

Deep dimensionality exchange is a new deep learning protocol developed at Expero for performing domain transfer between domains of different dimensions.

At Expero, TigerGraph’s 2020 projections are already in place or well underway.

Natural language processing is a powerful tool in building investigatory user interfaces for data exploration.

Data products are the deployed scalable, reproducible outcomes from a data science initiative. Realize ROI from data science and deliver value to end-users.

Use Machine Learning to increase volume, maintain profits and meet the needs of customers while maintaining a simple business policy.

A sequel to “Bush Pilots in the Outback”, we explore using reinforcement learning to schedule thousands at scale.

Learn how you can build a flexible data ingestion pipeline to handle highly varying data sources into your distributed NoSQL ecosystem.

One of Expero’s fraud detection techniques applied to the false prescription of opioids in clinical settings.

Using recurrent neural networks, we predict the spread of illness in the United States.

See how Reinforcement Learning can be used to optimize pickup and delivery schedules in an unpredictable environment.

Find dissatisfied customer cohorts and evaluate intervention measures using graph machine learning.

How to detect both credit card fraud and money laundering using graph and machine learning.

Leveraging the natural structure of data, graph convolutional networks produce optimal predictions of node properties.

FBI’s use of machine learning based entity resolution to catch criminals and fraudulent activity.

Can an AI learn to write better looking websites than a human? Frighteningly, yes.