Author Archives: Cy Jervis

About Cy Jervis

Community Manager Cloudera Community

Deep learning with Apache MXNet on Cloudera Data Science Workbench

Categories: CDH Cloudera Data Science Workbench Data Science

With the abundance of deep learning frameworks available today, it can be difficult to know what to choose for any particular application. Given the contrasting strengths and weaknesses of these frameworks, the ability to work with and switch between more than one is particularly important. Recent Cloudera blogs have shown how examples of applying deep learning on the Cloudera ecosystem using popular frameworks Deeplearning4j, BigDL, and Keras+TensorFlow.

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What’s New in Cloudera Director 2.6

Categories: CDH Cloud Cloudera Director

Cloudera Director 2.6 introduces support for protecting communications with TLS and SSH host keys. Azure support is enhanced with support for Azure Managed Disks and custom images..

Cloudera Director helps you deploy, scale, and manage Cloudera clusters in AWS, Azure, or Google Cloud Platform. Its enterprise-grade features deliver a mechanism for establishing production-ready clusters in the cloud for big-data workloads and applications in a simple, reliable, automated fashion.

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Understanding how Deep Learning learns to play SET®

Categories: CDH Cloudera Data Science Workbench Data Science

In the past few years, deep learning has seen incredible success in image recognition applications. In this post I examine how to train a convolutional neural network to recognize playing card images from a game called SET®, explore the structure of the model to get some insight into what it is “seeing”, and present a webcam application that uses the deployed model in a near-realtime setting.

SET is a card game where the objective is to find triples of cards,

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A Look at ADLS Performance – Throughput and Scalability

Categories: CDH Cloud Hadoop HDFS Performance

Overview

Azure Data Lake Store (ADLS) is a highly scalable cloud-based data store that is designed  for collecting, storing and analyzing large amounts of data, and is ideal for enterprise-grade applications.  Data can originate from almost any source, such as Internet applications and mobile devices; it is stored securely and durably, while being highly available in any geographic region.  ADLS is performance-tuned for big data analytics and can be easily accessed from many components of the Apache Hadoop ecosystem,

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Informatica Big Data Management on Cloudera Altus

Categories: CDH Cloud

Today, we’re really excited to announce the latest innovation from Cloudera and Informatica’s partnership. Companies are increasingly moving their data operations into the cloud. With both companies focusing on helping customers derive business insights out of vast amounts of data, our new joint offering will dramatically simplify leveraging cloud-native infrastructures for big data analytics.

Last May, Cloudera announced Cloudera Altus, a new platform-as-a-service (PaaS) offering in the cloud for big data analytics,

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