Software Alternatives & Reviews

Floyd VS Comet.ml

Compare Floyd VS Comet.ml and see what are their differences

Floyd logo Floyd

Heroku for deep learning

Comet.ml logo Comet.ml

Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
  • Floyd Landing page
    Landing page //
    2023-03-20
  • Comet.ml Landing page
    Landing page //
    2023-09-16

Floyd

Categories
  • AI
  • Data Science And Machine Learning
  • Machine Learning
  • Developer Tools
Website blog.floydhub.com

Comet.ml

Categories
  • Data Science And Machine Learning
  • Data Science Notebooks
  • Machine Learning Tools
  • Machine Learning
Website comet.com

Floyd videos

How to: Floyd Bed and Purple Mattress + Review (Not Sponsored)

More videos:

  • Review - Floyd Bed Frame Setup and Review - Is it Supportive Enough?
  • Review - FLOYD (FLAT PACK) REVIEW/UNBOXING | THE SOFA + THE COFFEE TABLE + THE FLOYD BED | APARTMENT BUNDLE

Comet.ml videos

Running Effective Machine Learning Teams: Common Issues, Challenges & Solutions | Comet.ml

More videos:

  • Review - Comet.ml - Supercharging Machine Learning

Category Popularity

0-100% (relative to Floyd and Comet.ml)
Data Science And Machine Learning
AI
100 100%
0% 0
Data Science Notebooks
0 0%
100% 100
Developer Tools
100 100%
0% 0

User comments

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What are some alternatives?

When comparing Floyd and Comet.ml, you can also consider the following products

Deep Learning Gallery - A curated list of awesome deep learning projects

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.

Lobe - Visual tool for building custom deep learning models

Weights & Biases - Developer tools for deep learning research

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.