Visualize dataset distributions with facets
This project is a GUI for the gpustack/gguf-parser-go
Display a Bokeh plot
Browse and filter LLM benchmark results
Analyze and visualize data with various statistical methods
Explore token probability distributions with sliders
Execute commands and visualize data
Display a welcome message on a webpage
Analyze and visualize car data
Generate a data report using the pandas-profiling tool
Check system health
Need to analyze data? Let a Llama-3.1 agent do it for you!
Evaluate diversity in data sets to improve fairness
Facets Overview is a powerful data visualization tool designed to help users better understand their datasets by breaking them down into smaller, manageable parts called facets. It provides insights into how data is distributed across different variables, making it easier to identify patterns, outliers, and relationships within the data.
What libraries or frameworks are required to use Facets Overview?
Facets Overview typically requires TensorFlow and TensorFlow Facets libraries, along with standard data manipulation tools like Pandas.
Can I use Facets Overview with any type of data?
Yes, Facets Overview supports categorical, numerical, and image data, making it versatile for various datasets.
How do I handle large datasets with Facets Overview?
For large datasets, use sampling or data aggregation techniques to improve performance while maintaining meaningful visualizations.
Is Facets Overview suitable for real-time data analysis?
While Facets Overview is primarily designed for offline analysis, it can handle near real-time data with proper setup and optimizations.