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 ...

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 ...

PALO ALTO, Calif., Feb. 9 — Cloudera, the global provider of the fastest, easiest, and most secure data management, analytics and machine learning platform built on the latest open source technologies ...

We called it Machine Learning October Fest. Last week saw the nearly synchronized breakout of a number of news centered around machine learning (ML): The release of PyTorch 1.0 beta from Facebook, ...

Finding insight in oceans of data is one of enterprises’ most pressing challenges, and increasingly AI is being brought in to help. Now, a new tool for Apache Spark aims to put machine learning within ...

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 ...

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 ...

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 ...

SAN FRANCISCO & AMSTERDAM--(BUSINESS WIRE)--Databricks, the leader in Unified Analytics and founded by the original creators of Apache Spark™, today announced that Spark + AI Summit returns to ...

Researchers at UC Berkeley’s RISELab have developed a new distributed framework designed to enable Python-based machine learning and deep learning workloads to execute in real-time with MPI-like power ...