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Deep Learning on Databricks – The Databricks Blog

We are excited to announce the general availability of Graphic Processing Unit (GPU) and deep learning support on Databricks! This blog post will help users get started via a tutorial with helpful tips and resources, aimed at data scientists and engineers who need to run deep learning applications at scale. What’s new? Databricks now offers a simple way to leverage GPUs to power image processing, text analy ...

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Build Apache Spark workflows with Databricks

Today we are excited to announce Notebook Workflows in Databricks. Notebook Workflows is a set of APIs that allow users to chain notebooks together using the standard control structures of the source programming language — Python, Scala, or R — to build production pipelines. This functionality makes Databricks the first and only product to support building Apache Spark workflows directly from notebooks, off ...

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Achieving End-to-end Security for Apache Spark with Databricks

Holistic Security for the Big Data Lifecycle Traditionally, enterprise organizations only had security solutions that addressed parts of their big data infrastructure. Today, enterprises demand holistic security that covers the full spectrum of their big data lifecycle: from file processing, big data clusters, code management, job workflows, application deployments, dashboards, to reports. The Databricks ju ...

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Comparing Cloud-based Machine Learning Platforms — Amazon ML vs Microsoft Azure ML vs Databricks (Spark) Cloud.

Introduction: In this blog post, data scientists at Third Eye Consulting Services will compare leading Cloud-based machine learning platforms. We will start with sharing the framework we used to compare the platforms and then we will apply the framework to compare Amazon ML, Microsoft Azure ML and Databricks Cloud. Updated as of: Mar’16 (Note that these services have an aggressive release cycle so if you’re ...

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The Unreasonable Effectiveness of Deep Learning on Spark

For the past three years, our smartest engineers at Databricks have been working on a stealth project. Today, we are unveiling DeepSpark, a major new milestone in Apache Spark. DeepSpark uses cutting-edge neural networks to automate the many manual processes of software development, including writing test cases, fixing bugs, implementing features according to specs, and reviewing pull requests (PRs) for the ...

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How real businesses are using machine learning

There is no question that machine learning is at the top of the hype curve. And, of course, the backlash is already in full force: I’ve heard that old joke “Machine learning is like teenage sex; everyone is talking about it, no one is actually doing it” about 20 times in the past week alone. But from where I sit, running a company that enables a huge number of real-world machine-learning projects, it’s clea ...

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FREE WEBINAR – Comparative Analysis of Cloud based Machine Learning Platforms

Machine Learning is seeing its day - every business in every domain is coming up with ways and means of incorporating Data Sciences for delivering business results. Answering the demands of the market, all major cloud vendors have released their own Machine Learning platforms to perform complex algorithms at the ease and scale of the clouds. This webinar discusses these platforms in detail while identifying ...

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Building a Recommendation Engine with Spark ML on Amazon EMR using Zeppelin – AWS Big Data Blog

Many developers want to implement the famous Amazon model that was used to power the "People who bought this also bought these items" feature on This model is based on a method called Collaborative Filtering. It takes items such as movies, books,  and that were rated highly by a set of users and recommending them to other users who also gave them high ratings. This method works well in domains w ...

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Build a CEP App on Apache Spark and Drools

Combining CDH with a business execution engine can serve as a solid foundation for complex event processing on big data.Event processing involves tracking and analyzing streams of data from events to support better insight and decision making. With the recent explosion in data volume and diversity of data sources, this goal can be quite challenging for architects to achieve.Complex event processing (CEP) is ...

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How Uber Uses Spark and Hadoop to Optimize Customer Experience

If you’ve ever used Uber, you’re aware of how ridiculously simple the process is. You press a button, a car shows up, you go for a ride, and you press another button to pay the driver. But there’s a lot more going on behind the scene, and much of that infrastructure increasingly runs on Hadoop and Spark, as the Uber data team recently shared.Uber has the envious position of sitting at the junction of the di ...

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