Articles
Entity resolution can be easy
Entity resolution using graphs and standard graph analytics is often sufficient for most customers.
Orbifold B.V.
Leuven, Belgium (Europe)
info@orbifold.net
orbifold.net
Google #TensorFlow has released a new Graph Neural Network library. Late to the party, with mature frameworks like #PyTorchGeometric, @GraphDeep and @stellargraph_io. https://t.co/WMM5t7mZDa #GraphMachineLearning https://t.co/uJNSReHFDw
5 Reasons Knowledge Graph will never bloom. https://t.co/NkfLdYt8dz #KnowledgeGraphs https://t.co/jiQ57w6j0B
Gartner has invented something called 'Sematic search' 😁 Anyhow, it's on the way out. Knowledge graphs are peaking. Graph machine learning does not exist in management consulting circles yet. https://t.co/kygfx4MAe2 #GraphAnalytics #KnowledgeGraphs https://t.co/dhqyXN9NKb
It's ridiculously easy to create node editors (visual programming anyone?) and other advanced UI's in Python using DearPyGui. Kudos to @jhoffs1 https://t.co/ygdX5xA2cq #Python https://t.co/rrLBD6rixE
Cylynx Motif; a new self-service, fully browser-based graph analytics tool with an open source branch. https://t.co/dFaFQumbzH #GraphAnalytics https://t.co/Ls1596xBn6 https://t.co/xWAVbQGfrN
Baffled by the speed of @RAPIDSai graph analytics and #DataScience in general. Faster than Spark, centrality of 5 million nodes in seconds. Kudos to the @dask_dev devs too for making things easy. You won a new fan here. https://t.co/Sal0hjMZNn #GraphAnalytics https://t.co/SfYCp1C53U
Large scale graph layout (with edge bundling), network visualizations and #dataviz on GPU thanks to @datashader. Perfectly complementing @RAPIDSai. https://t.co/mijYt1Lc1B https://t.co/hzf9moEIwU
AuraDS, the @neo4j data science stack in the cloud is in preview. https://t.co/9BWY7t7kJh #GraphDatabase https://t.co/d79x4UlhYp