Software Alternatives, Accelerators & Startups

FeedBear VS Azure Machine Learning Studio

Compare FeedBear VS Azure Machine Learning Studio and see what are their differences

FeedBear logo FeedBear

The smartest way to manage feedback from your customers

Azure Machine Learning Studio logo Azure Machine Learning Studio

Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.
  • FeedBear Landing page
    Landing page //
    2023-09-28

FeedBear helps you make informed product decisions and keep users in the loop.

  • Feedback boards allow you to collect feedback from your customers in one, central place.
  • Roadmap fills up automatically as you make progress.
  • Changelog allows you to make bigger announcements in a beautiful way.

Check out our website to learn more.

  • Azure Machine Learning Studio Landing page
    Landing page //
    2021-08-03

FeedBear

$ Details
paid Free Trial $59.0 / Monthly (All-inclusive)
Platforms
Web
Release Date
2018 August
Startup details
Country
Slovakia
City
Bratislava
Employees
1 - 9

FeedBear features and specs

  • Integrations: Intercom, Slack
  • Public roadmap: Show your progress
  • Feedback boards: Let your users post feedback & requests
  • Changelog: Announce important updates
  • Free Trial: 14-day free trial, no credit card required
  • Easy to Set-up and use: less than 5 min setup
  • Clean UI: Clean and Smooth UI, No technical jargon and just works

Azure Machine Learning Studio features and specs

No features have been listed yet.

FeedBear videos

No FeedBear videos yet. You could help us improve this page by suggesting one.

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Azure Machine Learning Studio videos

Azure Machine Learning Studio

More videos:

  • Review - Introduction to Microsoft Azure Machine Learning Studio & Services

Category Popularity

0-100% (relative to FeedBear and Azure Machine Learning Studio)
Customer Feedback
100 100%
0% 0
Data Science And Machine Learning
User Feedback
100 100%
0% 0
Machine Learning
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Azure Machine Learning Studio 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.

FeedBear mentions (0)

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

Azure Machine Learning Studio mentions (2)

  • What are all possible FREE Machine Learning integrations with Power BI?
    Machine Learning studio https://studio.azureml.net/ but this will be discontinued in Dec 01,2021 :(. Source: over 2 years ago
  • Stumbling into BI as a job role and need advice
    Advanced analytics, predictive modeling: You can't go passed learning R or Python if you're that way inclined.. however, if you're a GUI monkey like me, I have had a fair amount of success using https://studio.azureml.net/ it's free at base level :). Source: almost 3 years ago

What are some alternatives?

When comparing FeedBear and Azure Machine Learning Studio, you can also consider the following products

Canny - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Upvoty - User feedback in 1 simple overview 🔥

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.

Nolt - A fast & beautiful way to collect user feedback

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.