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  1. Initializing Dask Workers with cyBER... Initializing Dask Workers with cyBERT Model
    1
    from dask_cuda import LocalCUDACluster
    2
    from distributed import Client
    3
    import dask
    4
    
                  
    5
    def worker_init():
  2. Create Streamz Workflow for cyBERT Create Streamz Workflow for cyBERT
    1
    def inference(messages):
    2
        worker = dask.distributed.get_worker()
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        df = cudf.DataFrame()
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        if type(messages) == str:
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            df["stream"] = [messages.decode("utf-8")]
  3. Define Streamz Source for cyBERT Define Streamz Source for cyBERT
    1
    from streamz import Stream
    2
    consumer_conf = {
    3
            "bootstrap.servers": "localhost:9092",
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            "group.id": "group-1",
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            "session.timeout.ms": 60000,
  4. rapidsai/clx rapidsai/clx Public archive

    A collection of RAPIDS examples for security analysts, data scientists, and engineers to quickly get started applying RAPIDS and GPU acceleration to real-world cybersecurity use cases.

    Jupyter Notebook 168 68

  5. receptive_fields_via_spot_stim receptive_fields_via_spot_stim Public

    MATLAB

  6. NESC533 NESC533 Public

    Neural Network Modeling Class

    MATLAB