low-code ML dashboard builder
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Resultados para “un dashboard low-code para machine learning”
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- streamlit/streamlit
streamlit/streamlit
44,982Ver en GitHubStreamlit is a Python framework designed to transform data scripts into interactive web applications. It utilizes a reactive execution engine that automatically reruns scripts from top to bottom whenever a user interaction triggers a state change, ensuring the interface remains synchronized with the underlying data. By providing a declarative interface, it allows developers to build functional applications without requiring extensive knowledge of frontend web technologies. The framework distinguishes itself through an identity-based widget reconciliation system that persists user input across
Streamlit is a low-code Python framework for turning data scripts into interactive web apps, directly matching the need for building ML dashboards with minimal coding and strong visualization, model integration, and real-time interactivity.
PythonData Application FrameworksInteractive WidgetsExecution Models - gradio-app/gradio
gradio-app/gradio
42,931Ver en GitHubGradio is a Python library that enables the creation of interactive web applications by converting functions into browser-based interfaces. It functions as a declarative framework where developers define input and output components to automatically generate web forms, visualizations, and data-driven dashboards. By abstracting away manual web markup, the library allows for the rapid construction of interfaces for machine learning models, research demonstrations, and analytical workflows within a single environment. The platform distinguishes itself by automatically exposing internal applicatio
Gradio is a Python library that turns ML model functions into browser-based interfaces with minimal code, directly supporting data visualization, model integration, and sharing—exactly what you need for building ML dashboards without heavy coding.
PythonDeclarative UI FrameworksInteractive Interface BuildersModel Prototyping Tools - paddlepaddle/visualdl
PaddlePaddle/VisualDL
4,882Ver en GitHubVisualDL is a deep learning visualization toolkit and experiment tracking dashboard. It provides a web-based interface for monitoring training metrics, analyzing high-dimensional data, and rendering model architectures through static and dynamic graphs. The toolkit serves as a performance profiler to identify execution bottlenecks and optimize resource usage. It also functions as a data analyzer that uses projection algorithms to identify relationships between points in complex datasets. Capabilities include tracking training metrics via scalars and histograms, comparing multiple experiments
VisualDL is a web-based deep learning experiment tracking dashboard that lets you monitor training metrics, compare runs, and explore high-dimensional data with minimal coding — it fits the low-code ML dashboard builder category, though its primary focus is deep learning rather than general ML.
HTMLTraining Metric MonitorsVisualization ToolkitsDirected Graph Visualization
