Need advice about which tool to choose?Ask the StackShare community!

Deepo

0
14
+ 1
0
Kubeflow

180
546
+ 1
18
Add tool

Deepo vs Kubeflow: What are the differences?

Developers describe Deepo as "A Docker image containing almost all popular deep learning frameworks". Deepo is a Docker image with a full reproducible deep learning research environment. It contains most popular deep learning frameworks: theano, tensorflow, sonnet, pytorch, keras, lasagne, mxnet, cntk, chainer, caffe, torch. On the other hand, Kubeflow is detailed as "Machine Learning Toolkit for Kubernetes". 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.

Deepo and Kubeflow belong to "Machine Learning Tools" category of the tech stack.

Deepo and Kubeflow are both open source tools. It seems that Kubeflow with 7.04K GitHub stars and 1.03K forks on GitHub has more adoption than Deepo with 4.92K GitHub stars and 578 GitHub forks.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Deepo
Pros of Kubeflow
    Be the first to leave a pro
    • 9
      System designer
    • 3
      Google backed
    • 3
      Customisation
    • 3
      Kfp dsl

    Sign up to add or upvote prosMake informed product decisions

    - No public GitHub repository available -

    What is Deepo?

    Deepo is a Docker image with a full reproducible deep learning research environment. It contains most popular deep learning frameworks: theano, tensorflow, sonnet, pytorch, keras, lasagne, mxnet, cntk, chainer, caffe, torch.

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Deepo?
    What companies use Kubeflow?
      No companies found
      See which teams inside your own company are using Deepo or Kubeflow.
      Sign up for StackShare EnterpriseLearn More

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Deepo?
      What tools integrate with Kubeflow?

      Sign up to get full access to all the tool integrationsMake informed product decisions

      Blog Posts

      PythonDockerKubernetes+14
      11
      2247
      What are some alternatives to Deepo and Kubeflow?
      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.
      scikit-learn
      scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      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