ArangoBnB: Data Preparation Case Study

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This case study covers a data exploration and analysis scenario about modeling data when migrating to ArangoDB. The topics covered in this case study include:

  • Importing data into ArangoDB
  • Developing Application Requirements before modeling
  • Data Analysis and Exploration with AQL

This case study can hopefully be used as a guide as it shows step-by-step instructions and discusses the motivations in exploring and transforming data in preparation for a real-world application.
The information contained in this case study is derived from the development of the ArangoBnB project; a community project developed in JavaScript that is always open to new contributors. The project is an Airbnb clone with a Vue frontend and a React frontend being developed in parallel by the community. It is not necessary to download the project or be familiar with JavaScript for this guide. To see how we are using the data in a real-world project, check out the repository.

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ArangoML Series: Multi-Model Collaboration

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Multi-Model Machine Learning

This article looks at how a team collaborating on a real-world machine learning project benefits from using a multi-model database for capturing ML meta-data.

The specific points discussed in this article are how:

  • The graph data model is superior to relational for ML meta-data storage.
  • Storing ML experiment objects is natural with multi-model.
  • ArangoML promotes collaboration due to the flexibility of multi-model.
  • ArangoML provides ops logging and performance analysis.
ArangoML Pipeline Complete pipeline - ArangoDB Machine Learning
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ArangoML Series: Intro to NetworkX Adapter

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This post is the fifth in a series of posts introducing the ArangoML features and tools. This post introduces the NetworkX adapter, which makes it easy to analyze your graphs stored in ArangoDB with NetworkX.

In this post we:

  • Briefly introduce NetworkX
  • Explore the IMDB user rating dataset
  • Showcase the ArangoDB integration of NetworkX
  • Explore the centrality measures of the data using NetworkX
  • Store the experiment with arangopipe

This notebook is just a slice of the full-sized notebook available in the ArangoDB NetworkX adapter repository. It is summarized here to better fit the blog post format and provide a quick introduction to using the NetworkX adapter. 

ArangoML Pipeline Cloud graphic showing an example machine learning pipeline
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ArangoML Part 4: Detecting Covariate Shift in Datasets

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This post is the fourth in a series of posts introducing ArangoML and showcasing its benefits to your machine learning pipelines. Until now, we have focused on ArangoML’s ability to capture metadata for your machine learning projects, but it does much more. 

In this post we:

  • Introduce the concept of covariate shift in datasets
  • Showcase the built-in dataset shift detection API
ArangoML Pipeline Complete pipeline - ArangoDB Machine Learning
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