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Deep Learning with TensorFlow, GPUs, and Docker Containers

I work with a lot of data science teams at our enterprise customers, and in the past several months I’ve seen an increased adoption of machine learning and deep learning frameworks for a wide range of applications. As with other use cases in Big Data analytics and data science, these data science teams want to […] Read More

Deep Learning with BigDL and Apache Spark on Docker

The field of machine learning – and deep learning in particular – has made significant progress recently and use cases for deep learning are becoming more common in the enterprise. We’ve seen more of our customers adopt machine learning and deep learning frameworks for use cases like natural language processing with free-text data analysis, image […] Read More

Large-Scale Data Science Operations

Here at BlueData, I get the opportunity to meet with many data science teams working on very interesting projects in different industries across our customer base. These are definitely exciting times to be working in the field of data science, machine learning, and analytics. The primary goal of a data science team is to understand […] Read More

Distributed Data Science with Spark 2.0, Python, R, and H2O on Docker

Here at BlueData, I’ve worked with many of our customers (including large enterprises in financial services, telecommunications, and healthcare, as well as government agencies and universities) to help their data science teams with their Big Data initiatives. In this blog post, I want to share some of my recent experiences in working with the data […] Read More

App Workbench – Managing the Menagerie of Big Data Apps

One of the most challenging aspects of Big Data deployments is keeping up with the dynamic nature of Big Data frameworks, distributions, applications, and their latest versions. The success or failure of a Big Data implementation may hinge on how well the organization handles support for the menagerie of applications and tools that data scientists, […] Read More

Real-Time Data Pipelines with Spark, Kafka, and Cassandra (on Docker)

In my experience as a Big Data architect and data scientist, I’ve worked with several different companies to build their data platforms. Over the past year, I’ve seen a significant increase in focus on real-time data and real-time insights. It’s clear that real-time analytics provide the opportunity to make faster (and better) decisions and gain […] Read More