Search Results for "rich"

...The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. Additionally, data science often involve processes of data exploration, iterative modelling and interactive environments (mostly Jupyter notebook).

...Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. To create a base map, simply pass your starting coordinates to Folium. ...

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy. Visdom aims to facilitate visualization of (remote) data with an emphasis on supporting scientific experimentation. Broadcast visualizations of plots, images, and text for yourself and your collaborators. Organize your visualization space programmatically or through the UI to create dashboards for live data, inspect results of experiments, or debug experimental code. ...

GeoNotebook is an open-source extension to the Jupyter Notebook ecosystem that equips users with powerful geospatial visualization and analysis capabilities directly within the notebook interface. It integrates with GeoJS and other geospatial services to enable rich, interactive map rendering, layer control, and GIS data manipulation alongside traditional code and markdown cells in a Jupyter environment. Users can execute Python geospatial analysis and immediately visualize results on slippy web maps, allowing them to explore, annotate, and interpret large spatial datasets without leaving the notebook. ...

Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT), is a powerful and complete front-end to a rich set of visual-data exploration and analysis capabilities well suited for climate-data analysis problems.

The OpenCMISS-Zinc Library (opencmiss.org/zinc), or Zinc, is a software library for building interactive graphical modelling and visualisation applications. Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image...