Contributor: Rachel Silver

MapR Converge Blog author, Rachel Silver

Rachel Silver is the Technical Product Manager for the Hadoop Ecosystem at MapR. Prior to her position at MapR she has worked in the Big Data field as a Solutions Architect and Applications Engineer. Passionate about the intersection of data and humanity, Rachel is a big supporter of Open Source Software. Currently living in Pittsburgh, PA, she's enjoying the occasional ride in self-driving Ubers.

Blog Posts by Rachel Silver

January 14, 2019 | By Rachel Silver

Installing Kubeflow with MapR

In my previous blog in this series, Kubernetized Machine Learning and AI Using Kubeflow, I covered the Kubeflow project and how it integrates with and complements the MapR Data Platform. Kubeflow is an application deployment framework and software repo...

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August 28, 2018 | By Rachel Silver

Kubernetized Machine Learning and AI Using KubeFlow

In my previous blog, End-to-End Machine Learning Using Containerization, I covered the advantages of doing machine learning using microservices and how containerization can improve every step of the workflow by providing: Personalized Development Environments...

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June 28, 2018 | By Rachel Silver

End-to-End Machine Learning Using Containerization

Lately, we've been talking a lot about containerization and how Kubernetes and MapR can pair up to enhance the productivity of your data science teams and decrease the time to insights. In this multi-part blog series, I will start with a high-level...

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May 22, 2018 | By Rachel Silver

A Simple Architecture to Use AI/ML for Predictive Maintenance Success

Predictive maintenance (PdM) has emerged as a primary advanced analytics use case as manufacturers have sought increased operational efficiency and productivity and as a response to technological innovations like the Internet of Things (IoT) and edge...

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March 23, 2018 | By Rachel Silver

How To: Using R Studio with the MapR Data Science Refinery

MapR made a design goal to be both portable and extensible in this release to enable all types of data science teams. This means that, while we don't ship every possible tool that users will want, we have the right structure in place to allow them...

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February 28, 2018 | By Rachel Silver

Not [Wet]Dog: Agile Management of Dog and Model Training Needs

It was raining, and my dog was bugging me to go for a walk. So I asked, "What kind of dog wants to walk in the rain?" And then decided: I could use image classification to find out! Seems simple enough, right? At the time, I figured it would...

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February 09, 2018 | By Rachel Silver

Modern Python & PySpark Application Development on MapR

Python has become the darling language of the data science and data engineering world. It's versatile and powerful, yet easy enough for beginners to use. While we encounter Python developers in every area of IT from web development to network management...

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January 17, 2018 | By Rachel Silver

How To: Leveraging Python Environments from DSR (Conda)

At some point, you're going to need to run some of the popular new Python libraries that everybody is talking about, like MatPlotLib or SciPy. At this point, you may have noticed that it's not as simple as installing it on your local machine and...

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January 03, 2018 | By Rachel Silver

How To: Run the MapR Data Science Refinery from a Mac

Recently, MapR launched the MapR Data Science Refinery, a novel way to deliver data science functionality and connectivity for your MapR Data Platform. One of the great advantages to this product is the ability to deploy this workspace from wherever you...

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December 16, 2017 | By Rachel Silver

How To: Run the MapR Data Science Refinery from an Edge Node

Recently, MapR launched the MapR Data Science Refinery, a novel way to deliver data science functionality and connectivity for your MapR Data Platform. One of the great advantages to this is the ability to deploy this workspace from wherever you chose...

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December 04, 2017 | By Rachel Silver

How To: Using TensorFlow with the MapR Data Science Refinery

MapR made a design goal to be both portable and extensible in this release to enable all types of data science teams. This means that, while we don't ship every possible tool that users will want, we have the right structure in place to allow them...

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November 29, 2017 | By Rachel Silver

How To: Collaborate & Share Notebooks using the MapR Data Science Refinery

So, let's say you want to share your notebooks with a colleague or just utilize the persistent storage provided by MapR XD. How would you go about doing this? Convergence and portability are at the heart of our design of the MapR Data Science Refinery...

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October 24, 2017 | By Rachel Silver

Introducing the MapR Data Science Refinery

Data Science is a hot topic in boardrooms right now. Everybody wants to adopt AI/ML, hire the best and brightest data scientists, and enable them to experiment and build intelligent applications. New deep learning libraries have made it possible to analyze...

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June 29, 2017 | By Rachel Silver

Python Environments for PySpark, Part 1: Using Condas

Are you a data scientist, engineer, or researcher, just getting into distributed processing using PySpark? Chances are that you’re going to want to run some of the popular new Python libraries that everybody is talking about, like MatPlotLib. If so, you...

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April 10, 2017 | By Rachel Silver

Announcing: MEP 2.0.1, 1.1.2, and ECO-1703

We are pleased to announce the following two maintenance releases: MEP 2.0.1: a maintenance release for our MEP 2.0/community/ branch MEP 1.1.2: a maintenance release for our MEP 1.1/community/ branch ECO-1703: a maintenance release for our pre-MEP Eco...

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December 09, 2016 | By Rachel Silver

Announcing MapR Ecosystem Pack (MEP) 2.0!

We’re pleased to announce the general release of the MapR Ecosystem Pack (MEP) version 2.0. This represents the second major release of a MapR Ecosystem Pack since the beginning of this new process of delivering ecosystem upgrades. If you’re new to this...

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November 30, 2016 | By Rachel Silver

MapR Ecosystem Packs for Updating Ecosystem Components | Whiteboard Walkthrough

Editor's Note: Watch the on-demand webinar about the MapR Ecosystem Packs. In this week’s Whiteboard Walkthrough, Rachel Silver, Ecosystem Product Manager at MapR, talks about MapR Ecosystem Packs or MEPs that give you a convenient way to upgrade...

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October 26, 2016 | By Rachel Silver

An Application Blueprint for Financial Data

How to Use the Blueprint The blueprint consists of a sample financial services application that serves as a tutorial and starting point for a converged application that includes high speed streaming. Written for the MapR Data Platform, the application...

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September 27, 2016 | By Rachel Silver

Event-Driven Microservices on the MapR Data Platform

MapR is pleased to announce support for event-driven microservices on the MapR Data Platform. In this blog post, I’d like to explain what this means, and how it fits into our bigger idea of “convergence.” What are event-driven microservices? Microservices...

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August 11, 2016 | By Rachel Silver

MapR Ecosystem Pack (MEP) 1.0

Introduction Our first MapR Ecosystem Pack release, MEP 1.0, is now available through the MapR 5.2 Installer or the ecosystem repository. This release is only supported for MapR Core Release 5.2. MEP 1.0 Details The following is a list of components...

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August 11, 2016 | By Rachel Silver

MapR Ecosystem Packs Process

What are MapR Ecosystem Packs (MEPs)? We're excited today to announce the release of the MapR Ecosystem Packs process and our first MapR Ecosystem Pack (MEP). We'd like to go over how this will work and what you can expect from this process moving...

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