HCA: Predicting Patient Outcomes in Real-time with H2O

As the leading healthcare provider with 169 hostpials, 116 surgury centers, over 200,000 employees,and 26 mllion patient encounters per year, HCA is always looking for ways to improve patient care and manage costs. #ai #machinelearning #ai #deeplearning #ml 

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AI & Capital One: Preventing Downtime with Mobile Transaction Forecasing and Anomaly Detection

Mobile bankng is a key application for Capital One serving millions of customers per day. Predicting infrastructure issues before they become bottlenecks and impact customer transactions is a key goal of the technology operations group. Effective prediction requires has to scale across large datasets and take into account a variety of time series factors that […]

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TensorFlow Extended (TFX): Machine Learning Pipelines and Model Understanding (Google I/O’19)

This talk will focus on creating a production machine learning pipeline using TFX. Using TFX developers can implement machine learning pipelines capable of processing large datasets for both modeling and inference. In addition to data wrangling and feature engineering over large datasets, TFX enables detailed model analysis and versioning. The talk will focus on implementing […]

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June 28th, 2019

Google: The Anatomy of a Production-Scale Continuously-Training Machine Learning Platform

Creating and maintaining a platform for reliably producing and deploying machine learning models requires careful orchestration of many components—-a learner for generating models based on training data, modules for analyzing and validating both data as well as models, and finally infrastructure for serving models in production. This becomes particularly challenging when data changes over time […]

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June 28th, 2019