
Paperspace
Amazon Machine Learning
Hugging Face
Azure Machine Learning Service
Netmind Power
TensorFlow
Spell
Heroku for deep learning

Automated software dependency project health tracking
Which is more popular?
Based on our record, Deadpendency seems to be more popular. It has been mentioned 2 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | blog.floydhub.com | deadpendency.com |
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What each product offers, as listed by its team.


Possible disadvantages
Possible disadvantages
An editorial look at what each product does well and who it suits.


No analysis of Floyd yet.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
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How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using Floyd and Deadpendency. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Tracking Floyd since Mar 2021.
I created a tiny startup in Haskell which failed RIP. I decided to open source the code though. Source: over 3 years ago
I sometimes stream my Haskell work on deadpendency - https://www.twitch.tv/alistairbuzz. Source: over 5 years ago
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GPU cloud computing made easy. Effortless infrastructure for Machine Learning and Data Science
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Machine learning made easy for developers of any skill level
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The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
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Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.
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The Decentralised Machine Learning and AI platform
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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.
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