GraphPipe vs Kubeflow vs numericaal

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GraphPipe

2
15
+ 1
0
Kubeflow

140
450
+ 1
16
numericaal

0
16
+ 1
0
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Pros of GraphPipe
Pros of Kubeflow
Pros of numericaal
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      System designer
    • 3
      Customisation
    • 3
      Kfp dsl
    • 2
      Google backed
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      What is GraphPipe?

      GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations.

      What is Kubeflow?

      The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

      What is numericaal?

      numericaal automates model optimization and management so you can focus on data and training.

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      Jobs that mention GraphPipe, Kubeflow, and numericaal as a desired skillset
      Pinterest
      San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US
      Pinterest
      San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US
      What companies use GraphPipe?
      What companies use Kubeflow?
      What companies use numericaal?
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        What tools integrate with GraphPipe?
        What tools integrate with Kubeflow?
        What tools integrate with numericaal?
          No integrations found

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          Blog Posts

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          What are some alternatives to GraphPipe, Kubeflow, and numericaal?
          TensorFlow
          TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
          PyTorch
          PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
          Keras
          Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
          scikit-learn
          scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
          CUDA
          A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
          See all alternatives