1 个仓库
Awesome GitHub RepositoriesAccess Pattern Sampling
Generates datasets of possible access patterns to help identify missing or anomalous behavioral data.
Distinct from Access Pattern Monitors: Distinct from Access Pattern Monitors: generates synthetic or sampled pattern datasets for analysis rather than monitoring active runtime traffic.
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Awesome Access Pattern Sampling GitHub Repositories
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- microsoft/synapseml
microsoft/SynapseML
5,230在 GitHub 上查看SynapseML is an Apache Spark machine learning library designed for building and scaling machine learning workflows and data pipelines across distributed clusters. It serves as a distributed machine learning pipeline framework and a distributed inference engine for executing hardware-accelerated predictions and deep learning tasks on large-scale datasets. The project functions as a cloud AI integration layer, allowing users to apply pretrained artificial intelligence services for text, vision, and speech within distributed pipelines. It also includes a dedicated suite of tools for distributed
Generates datasets of possible access patterns to help identify behavioral anomalies.
Scalaaiapache-sparkazure
