AWS Posted June 7, 2022 Share Posted June 7, 2022 You can now run graph analytics and machine learning tasks on graph data stored in Amazon Neptune using an open-source Python integration that simplifies data science and ML workflows. With this integration, you can read and write graph data stored in Neptune using Pandas DataFrames in any Python environment, such as a local Jupyter notebook instance, Amazon SageMaker Studio, AWS Lambda, or other compute resources. From there, you can run graph algorithms, such as PageRank and Connected Components, using open-source libraries like iGraph, Network, and cuGraph. View the full article Quote Link to comment Share on other sites More sharing options...
.png.6dd3056f38e93712a18d153891e8e0fc.png.1dbd1e5f05de09e66333e631e3342b83.png.933f4dc78ef5a5d2971934bd41ead8a1.png)
Recommended Posts
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.