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2018 Europe Spark Ai Summit
文档数:
78
using apache spark structured streaming on azure databricks for predictive maintenance of coordinate measuring machines
powering nlu engine with apache spark to communicate
powering nlu engine
unifying stateoftheart ai and big data in apache spark
designing a horizontally scalable eventdriven big data architecture
rejecting the null hypothesis of apathetic retweeting of us politicians and splcdefined hate groups in the 2016 us presidential election
sparkmpi approaching the fifth paradigm
coops transformation from brick and mortar to ai
developing for the intelligent cloud and intelligent edge
sparklens understanding the scalability limits of spark applications
building streaming recommendation engines on apache spark
using azure databricks structured streaming and deep learning pipelines to monitor 1000 solar farms in real time
azure databricksapache spark as a service
scaling advanced analytics at shell
three stats pitfalls facing the new data scientist
interactionbased feature extraction how to convert your users activity into valuable features
lessons from the field episode ii applying best practices to your apache spark applications
building an implicit recommendation engine
ml at the edge building your production pipeline with apache spark and tensorflow
ai and machine learning for the connected home
geospatial analytics at scale with deep learning and apache spark
pytorch an ecosystem for deep learningsoumith chintala facebook ai
experience of running spark on kubernetes on openstack for high energy physics workloads
towards writing scalable big data applications
spreadsheets and spark
hudi largescale near realtime pipelines at uber
ai that cares about your broadband connection
accelerating ai results in the enterprise
ibm developer model asset exchange
recurrent neural networks for recommendations and personalization
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