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Kubeflow VS MCenter

Compare Kubeflow VS MCenter and see what are their differences

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Kubeflow logo Kubeflow

Kubeflow makes deployment of ML Workflows on Kubernetes straightforward and automated

MCenter logo MCenter

Machine Learning Operationalization
  • Kubeflow Landing page
    Landing page //
    2023-10-11
  • MCenter Landing page
    Landing page //
    2021-08-03

Kubeflow videos

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Kubeflow 0.6 Release Feature Review

More videos:

  • Review - Kubeflow @ApacheSpark Operator PR update with review feedback
  • Review - Sentiment Analysis using Kubernetes and Kubeflow

MCenter videos

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MCenter MIS Macedonia

Category Popularity

0-100% (relative to Kubeflow and MCenter)

Kubeflow

MCenter

Data Science And Machine Learning
36 36%
Data Science And Machine Learning
64% 64
Machine Learning Tools
30 30%
Machine Learning Tools
70% 70
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100
Developer Tools
100 100%
Developer Tools
0% 0

User comments

Share your experience with using Kubeflow and MCenter. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Kubeflow seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Kubeflow mentions (2)

  • The Bacalhau Vision – A Distributed Compute over Data Platform
    I'm David Aronchick - first non-founding PM on Kubernetes, co-founder of Kubeflow [1], and co-founder of the SAME project [2] - and we've spent the past year working on Bacalhau [3], an open source project to bring compute to data. We've recently opened up a public-hosted cluster (all runnable from colab in our docs [4]) and would love your feedback - you can see our vision at the attached blog post. Thanks!... - Source: Hacker News / about 1 year ago
  • An update on relationships between stocks - STATISTICS ROCKS! - Brought to you by the SuperstonkQuants 🦍🥼🔬🚀
    You have GitHub org and a Vue based website up and running already, so it seems like you have tech logistics covered. Just in case it's useful, I have experience with Kubernetes, which can help run computationally intense workloads (even if GPUs are needed) or provide a pool of compute for something like Kubeflow (kubeflow.org). Here if you want, feel free to ignore if you're all covered in this area - I'll be... Source: almost 3 years ago

MCenter mentions (0)

We have not tracked any mentions of MCenter yet. Tracking of MCenter recommendations started around Mar 2021.

What are some alternatives?

When comparing Kubeflow and MCenter, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Datatron - Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

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