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ZenML VS Supervisely

Compare ZenML VS Supervisely and see what are their differences

ZenML logo ZenML

Create reproducible machine learning pipelines

Supervisely logo Supervisely

Supervisely helps people with and without machine learning expertise to create state-of-the-art...
  • ZenML Landing page
    Landing page //
    2023-10-05
  • Supervisely Landing page
    Landing page //
    2023-08-06

ZenML videos

Karachi AI : Meetup 12 - MLOPS INTRODUCTION AND DEMO WITH ZENML (URDU/HINDI)

Supervisely videos

🛠️Basic annotation overview - Supervisely

More videos:

  • Review - Cars annotation in Supervisely: Polygons vs. AI powered tool
  • Tutorial - Yolo v3 Tutorial #2 - Object Detection Training Part 1 - Create a Supervisely Cluster

Category Popularity

0-100% (relative to ZenML and Supervisely)
Developer Tools
100 100%
0% 0
Data Labeling
0 0%
100% 100
AI
26 26%
74% 74
Data Science And Machine Learning

User comments

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

Based on our record, ZenML should be more popular than Supervisely. It has been mentiond 10 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.

ZenML mentions (10)

  • [D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
    Hey everyone! At ZenML, we released today an integration that allows users to train and deploy models from pipelines in a simple way. I wanted to ask the community here whether the example we showcased makes sense in a real-world setting:. Source: about 2 years ago
  • How we made our integration tests delightful by optimizing our GitHub Actions workflow
    As of early March 2022 this is the new CI pipeline that we use here at ZenML and the Feedback from my colleagues -- fellow engineers -- has been very positive overall. I am sure there will be tweaks, changes and refactorings in the future, but for Now, this feels Zen. - Source: dev.to / over 2 years ago
  • Ask HN: Who is hiring? (March 2022)
    ZenML is hiring for a Design Engineer. ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows. We’re looking for a Design Engineer with a multi-disciplinary skill-set who can take over the look and feel of... - Source: Hacker News / over 2 years ago
  • Ask HN: Who is hiring? (January 2022)
    ZenML | Developer Advocate | Full-time | Remote (Europe / UK) | [https://zenml.io](https://zenml.io) Hey! We are an open-source company and the pulse of [ZenML](https://github.com/zenml-io/zenml)'s community is our driving force! ZenML is a MLOps framework to create reproducible ML pipelines for production machine learning use-cases. As a Developer Advocate / 'Tech Evangelist', you will help us fulfil our mission... - Source: Hacker News / over 2 years ago
  • [P] ZenML: An extensible, open-source framework to create reproducible machine learning pipelines
    GitHub: https://github.com/zenml-io/zenml (A star would be appreciated!). Source: over 2 years ago
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Supervisely mentions (6)

  • Way to label yolov7 images fast
    Another annotation tool that integrates prediction and training within the application is supervisely supervisely.com., unfortunately it's pretty expensive unless you are satisfied with the community version. I saw that they have an integration for owl-vit, which might be helpful for annotation of animals. https://ecosystem.supervisely.com/apps/serve-owl-vit. Source: about 1 year ago
  • 65 Blog Posts to Learn Data Science
    Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use Keras and Supervisely for this problem. This guide is for anyone who is interested in using Deep Learning for text recognition in images but has no idea where to start. - Source: dev.to / over 1 year ago
  • Bounding Box for Text Annotation
    If they were videos, I would have suggested trying supervise.ly as it has a very good tracking functionality. Source: almost 2 years ago
  • CVAT alternatives for video frame annotation
    Hi, I'm exactly in the same boat like you are. I looked around for a while and the better solutions I found was supervise.ly and CVAT for video annotation. The pricetag on supervisely is pretty high, so I analyzed CVAT for a couple days and was positively surprised. Source: almost 2 years ago
  • Accessing 2022 Machine Learning Imagery from WPI's Photo Album
    Under the WPI Photo Ambum section of the page for FRC field photos (https://www.firstinspires.org/robotics/frc/playing-field#WPIPhotos), they have a section of machine learning imagery. However, this link goes to supervise.ly, the website they use for machine learning. I created an account to attempt to download the images, however, whenever I try to 'clone' the project, it stalls at 0% and gives me an error... Source: about 2 years ago
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What are some alternatives?

When comparing ZenML and Supervisely, you can also consider the following products

Attri - Attri helps companies become AI-first organizations with research in the AI field, designing and applying AI processes, platforms, and solutions for success.

Labelbox - Build computer vision products for the real world

PrimeHub - PrimeHub provides a ready-to-use research and training environment for data scientists to focus on their true productivity in a collaborative environment.

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

Katonic MLOps Platform - Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place.​​

CrowdFlower - Enterprise crowdsourcing for micro-tasks