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Pros & Cons summary

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Prominent pros & cons

PROS

Pros:
Intuitive and user-friendly interface.
Comprehensive suite of ML algorithms supporting both supervised and unsupervised learning.
Robust set of automation tools for data preprocessing, model selection, and hyperparameter optimization.
Scalability and flexibility with cloud-based infrastructure.
Strong collaborative features that allow for easy sharing and management of models among team members.

CONS

Cons:
Limited customization options for advanced users.
Can be expensive for small businesses or individuals.
Some users find the interface not as user-friendly for beginners.
 

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BigML Cons review quotes

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