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Pipelines VS Polyaxon

Compare Pipelines VS Polyaxon and see what are their differences

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Pipelines logo Pipelines

Pipelines Inc.

Polyaxon logo Polyaxon

Get familiar with Polyaxon - Open source machine learning on Kubernetes, deep Learning on Kubernetes.
  • Pipelines Landing page
    Landing page //
    2023-08-27
  • Polyaxon Landing page
    Landing page //
    2022-07-09

Pipelines videos

+ Add

Are New Pipelines Doomed? Oil & Gas Delivery Explained

More videos:

  • Review - Using the Review Recipe for Purchases & Pipelines

Polyaxon videos

+ Add

Scaling and reproducing deep learning on Kubernetes with Polyaxon - Mourad Mourafiq

More videos:

  • Review - Scalable Deep Learning on Kubernetes with Polyaxon (Interview)
  • Review - Polyaxon v1.1.6

Category Popularity

0-100% (relative to Pipelines and Polyaxon)

Pipelines

Polyaxon

Data Science And Machine Learning
40 40%
Data Science And Machine Learning
60% 60
Continuous Integration
100 100%
Continuous Integration
0% 0
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100
DevOps Tools
100 100%
DevOps Tools
0% 0

User comments

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

Based on our record, Polyaxon seems to be more popular. It has been mentiond 4 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.

Pipelines mentions (0)

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

Polyaxon mentions (4)

  • Any MLOps platform you use?
    If you're not concerned about self-hosting, WandB is one of the more fully featured training monitoring tools (I've used it in the past without any issues but the lack of data and training privacy and lack of self-hosting possibilities makes it a hard no for anything that isn't scholastic). Polyaxon is an alternative but rewriting all your variable logging to conform to their requirements makes it very difficult... Source: about 1 year ago
  • [D] Kubernetes for ML - how are y'all doing it?
    We use Polyaxon and it’s pretty good. Source: about 2 years ago
  • [D] Productionalizing machine learning pipelines for small teams
    For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases. Source: almost 3 years ago
  • [D] MLOps Platform Comparison and Preference (Kubeflow/MLFlow/Metaflow/MLRun/Gradient/Valohai/Others)
    I would also look into https://polyaxon.com/, I have used it on AWS and GCP the free open source version:. Source: about 3 years ago

What are some alternatives?

When comparing Pipelines and Polyaxon, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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.

CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.

H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

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