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Why Your Models Are Getting Lost in Translation

Ginger Phelps July 25, 2017
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Currently there are innumerable data languages that can be used for a wide range of analytic projects, and this amount will surely increase as new languages are being developed.

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The Evolution from PMML and PFA to Agnostic Scoring Engines

Ginger Phelps July 18, 2017
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Before models can be placed into scoring engines and then into production, custom code has to be written for each model. This process is labor-intensive and often error-prone. After the model’s custom code is written, Data Scientists have to transport the model to IT.  

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Welcome Rehgan Avon to Open Data Group

Ginger Phelps July 17, 2017
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RehganAvon.pngWe are excited to introduce Rehgan Avon as the newest addition to the Open Data Group (ODG) team.  Rehgan comes on board as a Product Manager, with a background in integrated systems engineering and a strong focus on analytical technology.  She has easily made the transition from data and systems engineering to product strategy.

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How To Score Big Data At Scale

Ginger Phelps July 12, 2017
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Modern businesses leverage analytics to gain insights in a multitude of areas, from evaluating business performance to predicting future behaviors. In many industries, these insights are quantified numerically as “scores,” and the process of applying an analytic model to transform a collection of data into scores is called “scoring.”

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Ideas Through Creating Value: How do we get there?

Ginger Phelps July 6, 2017
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Imagine that you created a model that runs without any errors. There were no miscalculations the first time Data Science tested it, IT could easily read and replicate it, and it was deployed within a few hours of being trained and approved. In a perfect world, this process may be a bit more realistic. However, this ease of creating a well-performing model is not always seen.  

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The Importance of Rapid Iteration

Ginger Phelps June 28, 2017
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Software engineers are always looking for new, fast ways to update their models once deployed into production. Whether this involves running a new system, creating a new code, or utilizing a new software, programmers need to find fast and accurate ways to update their models that are already in production in order to maintain efficiency.

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Top 5 Reasons Why The Cloud Matters

Ginger Phelps June 22, 2017
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Cloud computing has forever changed the way businesses have been storing and managing their data. Within the past few years, many companies have made the switch from storing their data within a service oriented architecture (SOA) to the cloud. 

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3 Ways Model Management Helps You Get Organized

Ginger Phelps June 20, 2017
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Imagine tracking data for multiple models by hand. How long would this process take you? Hours? Days? This question mainly depends on how many models you need to track and how much information there needs to be maintained within the models.

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How to Install Docker and FastScore in a Blank System [VIDEO]

Blair Fleming June 16, 2017
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Install Docker and FastScore in 5 minutes!

Want to install FastScore but not sure how to get it up and running?  Watch this 5 minute instructional video with George Kharchenko from our data science team and walk through how to install both Docker and FastScore into your blank system.  The video will lead you through what prerequisites you will need, as well as how to configure the FastScore fleet, and more.

  • How to install python and set-up tools
  • Installing Docker and FastScore CLI
  • Launch model manage and install the FastScore Fleet

Docker Containers allow for easy install and set-up of FastScore.  Once installed you can view the dashboard and start scoring models in minutes. 

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Why Agnostic Software Is Important

Ginger Phelps June 15, 2017
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Programming has redefined itself over the years from simply writing code to now finding effective solutions to any problem related to software development, algorithm, analytics, etc. These solutions have required the help of various software tools that are not always compatible with one another.

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