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Spell VS Comet.ml

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

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Spell logo Spell

Deep Learning and AI accessible to everyone

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.
  • Spell Landing page
    Landing page //
    2022-09-23
  • Comet.ml Landing page
    Landing page //
    2023-09-16

Spell videos

+ Add

Love Spells 24 Reviews 💙 My experience with their spells (excited to share)

More videos:

  • Review - SPELL Opulent Decay Album Review | Overkill Reviews
  • Review - LETS REVIEW Spells That Work

Comet.ml videos

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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 Spell and Comet.ml)

Spell

Comet.ml

Data Science And Machine Learning
58 58%
Data Science And Machine Learning
42% 42
AI
100 100%
AI
0% 0
Data Science Notebooks
45 45%
Data Science Notebooks
55% 55
Developer Tools
100 100%
Developer Tools
0% 0

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What are some alternatives?

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

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.

Neuton.AI - No-code artificial intelligence for all

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.

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Weights & Biases - Developer tools for deep learning research

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.

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