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As organizations create more diverse and more user-focused data products and services, there is a growing need for machine learning, which can be used to develop personalizations, recommendations, and ...

Paraphrasing Garrison Keillor, it's been a quiet week in the Apache Spark community - at least compared to last year, where the definitive Spark 2.0 was unveiled. Last week, Spark Summit pulled into ...

As I wrote in March of this year, the Databricks service is an excellent product for data scientists. It has a full assortment of ingestion, feature selection, model building, and evaluation functions ...

This article describes the journey of the migration towards a Federated GraphQL architecture. Specifically, it shows the GraphQL platform Netflix has built consisting of the Domain Graph Services ...

The AMPLab this week announced the release of KeystoneML, a framework for building and deploying large-scale machine-learning pipelines within Apache Spark. While the software is still in alpha stage, ...

Databricks Inc., the primary commercial steward behind the popular open source Apache Spark data processing framework for Big Data analytics, published a new report indicating the technology is still ...

This report focuses on how to tune a Spark application to run on a cluster of instances. We define the concepts for the cluster/Spark parameters, and explain how to configure them given a specific set ...

This article was originally published on ETFTrends.com. Watch a complimentary webinar below to learn more about Apache Spark’s MLlib, which makes machine learning scalable and easier with ML pipelines ...

New York City's historical buildings, businesses and sensibilities - some of them decades old - have been under siege for the past few years. One of the latest victims is the historic Waldorf Astoria ...