Cluster data points using KMeans
Leaderboard for text-to-video generation models
Check your progress in a Deep RL course
Browse and explore datasets from Hugging Face
Select and analyze data subsets
Check system health
Explore how datasets shape classifier biases
Execute commands and visualize data
Generate a detailed dataset report
Visualize dataset distributions with facets
Generate plots for GP and PFN posterior approximations
Search for tagged characters in Animagine datasets
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
Gradio Pyscript is a powerful tool for data visualization that allows users to interactively visualize and cluster data points using the KMeans algorithm. It provides a seamless way to work with data, enabling users to explore and understand patterns within their datasets through an intuitive interface.
• Interactive Visualization: Directly visualize data points and clusters in an interactive plot.
• KMeans Clustering: Perform clustering using the KMeans algorithm with adjustable parameters.
• Real-time Updates: Adjust parameters (e.g., number of clusters) and see results in real-time.
• User-friendly Interface: Designed for ease of use, with sliders and controls for customization.
• Data Export: Save the visualized results as images or data for further analysis.
import gradio as gr
import pandas as pd
from sklearn.cluster import KMeans
What algorithms does Gradio Pyscript support?
Gradio Pyscript primarily supports KMeans clustering, but it can be extended to work with other clustering algorithms.
How large of a dataset can Gradio Pyscript handle?
Gradio Pyscript is optimized for moderately sized datasets. For very large datasets, performance may degrade, and additional optimizations may be required.
Can I save the visualized clusters?
Yes, Gradio Pyscript allows you to export visualizations as images or retrieve the cluster data for further analysis.