Who’s Who in Data Science
Estimated reading time: 10 minutes
Multiple data science personas participate in the daily operations of data logistics and intelligent business applications. Management and employees need to understand the big picture of data science to maximize collaboration efforts for these operations. This article will highlight the specialized roles and skillsets needed for the different data science tasks and the best tools to empower data-driven teams. You will come away from this article with a better understanding of how to support your own data science teams, and it is valuable for both managers and team members alike.
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Integrate ArangoDB with PyTorch Geometric to Build Recommendation Systems
Estimated reading time: 20 minutes
In this blog post, we will build a complete movie recommendation application using ArangoDB and PyTorch Geometric. We will tackle the challenge of building a movie recommendation application by transforming it into the task of link prediction. Our goal is to predict missing links between a user and the movies they have not watched yet.
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Introducing the new ArangoDB Datasource for Apache Spark
Estimated reading time: 8 minutes
We are proud to announce the general availability of ArangoDB Datasource for Apache Spark: a new generation Spark connector for ArangoDB.
Nowadays, Apache Spark is one of the most popular analytics frameworks for large-scale data processing. It is designed to process in parallel data that is too large or complex for traditional databases, providing high performances by optimizing query execution, caching data in-memory and controlling the data distribution.
(more…)Introducing ArangoDB 3.9 – Graph Meets Analytics
Estimated reading time: 4 minutes
We are proud to announce the GA release of ArangoDB 3.9!
Congrats to the team and community for the latest ArangoDB release 3.9! ArangoDB 3.9 is focused on extending the capabilities of advanced Analytics and especially at scaling Graph use cases even further. In the remainder of this blog post, we will dive further into some of the features including Hybrid SmartGraphs, new AQL functions, new ArangoSearch Analyzer, and various other performance and user experience improvements.
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Introducing the ArangoDB-DGL Adapter
Estimated reading time: 15 minutes
We are proud to announce the GA 1.0 release of the ArangoDB-DGL Adapter!
The ArangoDB-DGL Adapter exports Graphs from ArangoDB, a multi-model Graph Database, into Deep Graph Library (DGL), a python package for graph neural networks, and vice-versa.
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