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Data Sources Integration: MindsDB seamlessly integrates with various data sources, including traditional databases and data behind APIs. When you query a data source, MindsDB forwards the query in real-time to the original data source. It excels at translating SQL to other query dialects1. Benefits: Unified Deployment: No need for custom, complex data pipelines or separate systems for AI/ML deployment. Automated Workflows: MindsDB automates the entire AI workflow based on time-based or event-based triggers2. AI/ML Frameworks Integration: MindsDB supports a wide range of AI/ML modeling possibilities, from Generative AI to traditional ML and AutoML. You can create, train, and deploy models within the MindsDB ecosystem using data from connected sources1. Considerations: Model Selection: Enhance the framework’s model selection capabilities. Hyperparameter Tuning: Provide automated hyperparameter tuning. Feature Engineering: Explore automated feature engineering options. Community Contributions: MindsDB’s community welcomes contributions. If you’re interested, you can even create new handler integrations into the MindsDB codebase. This collaborative spirit drives continuous improvement and innovation
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Short description and motivation for the proposed feature
Data Sources Integration:
MindsDB seamlessly integrates with various data sources, including traditional databases and data behind APIs. When you query a data source, MindsDB forwards the query in real-time to the original data source. It excels at translating SQL to other query dialects1.
Benefits:
Unified Deployment: No need for custom, complex data pipelines or separate systems for AI/ML deployment.
Automated Workflows: MindsDB automates the entire AI workflow based on time-based or event-based triggers2.
AI/ML Frameworks Integration:
MindsDB supports a wide range of AI/ML modeling possibilities, from Generative AI to traditional ML and AutoML. You can create, train, and deploy models within the MindsDB ecosystem using data from connected sources1.
Considerations:
Model Selection: Enhance the framework’s model selection capabilities.
Hyperparameter Tuning: Provide automated hyperparameter tuning.
Feature Engineering: Explore automated feature engineering options.
Community Contributions:
MindsDB’s community welcomes contributions. If you’re interested, you can even create new handler integrations into the MindsDB codebase. This collaborative spirit drives continuous improvement and innovation
Video or screenshots
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Describe some possible solutions
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Anything else?
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The text was updated successfully, but these errors were encountered: